Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/46 - Arrangements for interfacing with the operator or the patient
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Goods & Services

Software as a service (SaaS) services featuring software for generating, analyzing, and managing cardiovascular diagnostic aid, assessments, predictions, risk stratification, and reporting based on medical images; design, development, programming, updating, maintenance, and customization of cardiovascular medical imaging software, including platforms utilizing artificial intelligence and machine learning Providing software-based cardiovascular imaging aid services for medical purposes, including image-based cardiovascular examination, assessment, monitoring, reporting, triage, and risk evaluation to aid in diagnosis; providing cardiovascular medical imaging, screening, information, consultation, and advisory services, including the use of software or artificial intelligence to support and aid medical analysis and decision-making

Goods & Services

Software as a service (SaaS) services featuring software for generating, analyzing, and managing cardiovascular diagnostic aid, assessments, predictions, risk stratification, and reporting based on medical images; design, development, programming, updating, maintenance, and customization of cardiovascular medical imaging software, including platforms utilizing artificial intelligence and machine learning; and software as a service (SaaS) services for prioritizing or triaging cardiovascular imaging cases and managing related patient information Providing software-based cardiovascular imaging aid services for medical purposes, including image-based cardiovascular examination, assessment, monitoring, reporting, triage, and risk evaluation to aid in diagnosis; providing cardiovascular medical imaging, screening, information, consultation, and advisory services, including the use of software or artificial intelligence to support and aid medical analysis and decision-making

Goods & Services

Software as a service (SaaS) services featuring software for generating, analyzing, and managing cardiovascular diagnostic aid, assessments, predictions, risk stratification, and reporting based on medical images; design, development, programming, updating, maintenance, and customization of cardiovascular medical imaging software, including platforms utilizing artificial intelligence and machine learning; and software as a service (SaaS) services for managing cardiovascular imaging cases and related patient information Providing software-based cardiovascular imaging aid services for medical purposes, including image-based cardiovascular examination, assessment, monitoring, reporting, and risk evaluation to aid in diagnosis; providing cardiovascular medical imaging, screening, information, consultation, and advisory services, including the use of software or artificial intelligence to support and aid medical analysis and decision-making

Goods & Services

Software as a service (SaaS) services featuring software for generating, analyzing, and managing cardiovascular diagnostic aid, assessments, predictions, risk stratification, and reporting based on medical images; design, development, programming, updating, maintenance, and customization of cardiovascular medical imaging software, including platforms utilizing artificial intelligence and machine learning; and software as a service (SaaS) services for prioritizing or triaging cardiovascular imaging cases and managing related patient information Providing software-based cardiovascular imaging aid services for medical purposes, including image-based cardiovascular examination, assessment, monitoring, reporting, triage, and risk evaluation to aid in diagnosis; providing cardiovascular medical imaging, screening, information, consultation, and advisory services, including the use of software or artificial intelligence to support and aid medical analysis and decision-making

Goods & Services

Software as a service (SaaS) services featuring software for generating, analyzing, and managing cardiovascular diagnostic aid, assessments, predictions, risk stratification, and reporting based on medical images; design, development, programming, updating, maintenance, and customization of cardiovascular medical imaging software, including platforms utilizing artificial intelligence and machine learning; and software as a service (SaaS) services for prioritizing or triaging cardiovascular imaging cases and managing related patient information Providing software-based cardiovascular imaging aid services for medical purposes, including image-based cardiovascular examination, assessment, monitoring, reporting, triage, and risk evaluation to aid in diagnosis; providing cardiovascular medical imaging, screening, information, consultation, and advisory services, including the use of software or artificial intelligence to support and aid medical analysis and decision-making

Goods & Services

Software as a service (SAAS) services featuring software for generating cardiovascular diagnostics aid based on medical images; software as a service (SAAS) services featuring software for generating cardiovascular diagnostics aid based on medical images and machine learning; software as a service (SAAS) services featuring software for cardiovascular imaging, namely, for interpreting the results of cardiovascular medical imaging scans Image-based cardiovascular analysis services for medical diagnostic and treatment purposes; cardiovascular analysis testing, monitoring, and reporting services for medical diagnostic and treatment purposes; cardiovascular analysis for diagnostic or treatment purposes; cardiovascular image analysis services for medical diagnostic and treatment purposes; cardiovascular medical information; cardiovascular medical screening; cardiovascular medical advisory services; providing cardiovascular medical information

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/46 - Arrangements for interfacing with the operator or the patient
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/46 - Arrangements for interfacing with the operator or the patient
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/46 - Arrangements for interfacing with the operator or the patient
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Goods & Services

Software as a service (SAAS) services featuring software for generating cardiovascular diagnostics aid based on medical images; Software as a service (SAAS) services featuring software for generating cardiovascular diagnostics aid based on medical images and machine learning; Software as a service (SAAS) services featuring software for cardiovascular imaging, namely, for interpreting the results of cardiovascular medical imaging scans Image-based cardiovascular analysis services for medical diagnostic and treatment purposes; cardiovascular analysis testing, monitoring, and reporting services for medical diagnostic and treatment purposes; cardiovascular analysis for diagnostic or treatment purposes; cardiovascular image analysis services for medical diagnostic and treatment purposes; cardiovascular medical information; cardiovascular medical screening; cardiovascular medical advisory services; providing cardiovascular medical information

Goods & Services

Software as a service (SAAS) services featuring software for generating cardiovascular diagnostics aid based on medical images; Software as a service (SAAS) services featuring software for generating cardiovascular diagnostics aid based on medical images and machine learning; Software as a service (SAAS) services featuring software for cardiovascular imaging, namely, for interpreting the results of cardiovascular medical imaging scans Image-based cardiovascular analysis services for medical diagnostic and treatment purposes; cardiovascular analysis testing, monitoring, and reporting services for medical diagnostic and treatment purposes; cardiovascular analysis for diagnostic or treatment purposes; cardiovascular image analysis services for medical diagnostic and treatment purposes; cardiovascular medical information; cardiovascular medical screening; cardiovascular medical advisory services; providing cardiovascular medical information

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/46 - Arrangements for interfacing with the operator or the patient
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

Systems and methods of facilitating determination of risk of coronary artery disease (CAD) based at least in part on one or more measurements derived from non-invasive medical image analysis. The methods can include accessing a non-invasive generated medical image, identifying one or more arteries, identifying, regions of plaque within an artery, analyzing the regions of plaque to identify low density non-calcified plaque, non-calcified plaque, or calcified plaque based at least in part on density, determining a distance from identified regions of low density non-calcified plaque to one or more of a lumen wall or vessel wall, determining embeddedness of the regions of low density non-calcified plaque by one or more of non-calcified plaque or calcified plaque, determining a shape of the more regions of low density non-calcified plaque, and generating a display of the analysis to facilitate determination of one or more of a risk of CAD of the subject.

IPC Classes  ?

• G06T 7/00 - Image analysis
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume

Abstract

This disclosure relates to systems, methods, and devices for plaque analysis, vessel and fluid flow analysis, and/or risk determination or prediction thereof. Some embodiments relate to determining fractional flow reserve (FFR) values. Some embodiments relate to determining FFR values using 3D-printed models. Some embodiments relate to identifying thin cap fibroatheroma based on analysis of computed tomography (CT) imaging. Some embodiments relate adjusting calcified plaque thresholds for CT images to address effects of calcium blooming.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 6/03 - Computed tomography [CT]

Abstract

This disclosure relates to systems, methods, and devices for plaque analysis, vessel and fluid flow analysis, and/or risk determination or prediction thereof. Some embodiments relate to determining fractional flow reserve (FFR) values. Some embodiments relate to determining FFR values using 3D-printed models. Some embodiments relate to identifying thin cap fibroatheroma based on analysis of computed tomography (CT) imaging. Some embodiments relate adjusting calcified plaque thresholds for CT images to address effects of calcium blooming.

IPC Classes  ?

• G06T 7/00 - Image analysis
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/246 - Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
• G06T 7/60 - Analysis of geometric attributes
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/46 - Arrangements for interfacing with the operator or the patient
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 40/14 - Vascular patterns

Abstract

This application is directed to systems, methods, and devices for image based analysis of plaque. In some embodiments, the approaches herein can be used for developing treatment plans, which can include local treatment, systemic treatment, or both. In some embodiments, the approaches herein can be used for stent selection. In some embodiments, the approaches herein can be used for surgical planning, which can include robotic surgical planning. In some embodiments, the approaches herein can be used for image normalization. In some embodiments, the approaches herein can be used for identifying plaque calcification thresholds. In some embodiments, the approaches herein can be used for identifying thin cap fibroatheroma. In some embodiments, the approaches herein can be used for coronary artery tree reconstruction. Some embodiments are directed to coronary artery disease risk stratification.

IPC Classes  ?

• G06T 7/00 - Image analysis
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/02 - Arrangements for diagnosis sequentially in different planesStereoscopic radiation diagnosis
• A61B 6/03 - Computed tomography [CT]
• A61B 6/42 - Arrangements for detecting radiation specially adapted for radiation diagnosis
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 5/60 - Image enhancement or restoration using machine learning, e.g. neural networks
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/766 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using regression, e.g. by projecting features on hyperplanes
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/46 - Arrangements for interfacing with the operator or the patient
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 40/14 - Vascular patterns

Abstract

A method for characterization of coronary plaque tissue data and perivascular tissue data using image data gathered from a computed tomography (CT) scan along a blood vessel, the image information including radiodensity values of coronary plaque and perivascular tissue located adjacent to the coronary plaque, the method comprising quantifying radiodensity in regions of coronary plaque, quantifying, radiodensity in at least one region of corresponding perivascular tissue adjacent to the coronary plaque, determining gradients of the quantified radiodensity values within the coronary plaque and the quantified radiodensity values within the corresponding perivascular tissue, and determining a ratio of the quantified radiodensity values within the coronary plaque and the corresponding perivascular tissue; and characterizing the coronary plaque by analyzing a gradient of the quantified radiodensity values in the coronary plaque and the corresponding perivascular, and/or the ratio of the coronary plaque radiodensity values and the radiodensity values of the corresponding perivascular tissue.

IPC Classes  ?

• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• G06T 7/00 - Image analysis

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 40/14 - Vascular patterns

Goods & Services

Software as a service (SAAS) services featuring software for generating cardiovascular diagnostics aid based on medical images; software as a service (SAAS) services featuring software for generating cardiovascular diagnostics aid based on medical images and machine learning; software as a service (SAAS) services featuring software for cardiovascular imaging, namely, for interpreting the results of cardiovascular medical imaging scans.

Goods & Services

Software as a service (SAAS) services featuring software for generating cardiovascular diagnostics aid based on medical images; software as a service (SAAS) services featuring software for generating cardiovascular diagnostics aid based on medical images and machine learning; software as a service (SAAS) services featuring software for cardiovascular imaging, namely, for interpreting the results of cardiovascular medical imaging scans Image-based cardiovascular analysis services for medical diagnostic and treatment purposes; cardiovascular analysis testing, monitoring, and reporting services for medical diagnostic and treatment purposes; cardiovascular analysis for diagnostic or treatment purposes; cardiovascular image analysis services for medical diagnostic and treatment purposes; cardiovascular medical information; cardiovascular medical screening; cardiovascular medical advisory services; providing cardiovascular medical information

Goods & Services

Software as a service (SAAS) services featuring software for generating cardiovascular diagnostics aid based on medical images; software as a service (SAAS) services featuring software for generating cardiovascular diagnostics aid based on medical images and machine learning; software as a service (SAAS) services featuring software for cardiovascular imaging, namely, for interpreting the results of cardiovascular medical imaging scans Image-based cardiovascular analysis services for medical diagnostic and treatment purposes; cardiovascular analysis testing, monitoring, and reporting services for medical diagnostic and treatment purposes; cardiovascular analysis for diagnostic or treatment purposes; cardiovascular image analysis services for medical diagnostic and treatment purposes; cardiovascular medical information; cardiovascular medical screening; cardiovascular medical advisory services; providing cardiovascular medical information

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/46 - Arrangements for interfacing with the operator or the patient
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/46 - Arrangements for interfacing with the operator or the patient
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

This application is directed to systems, methods, and devices for image based analysis of plaque. In some embodiments, the approaches herein can be used for developing treatment plans, which can include local treatment, systemic treatment, or both. In some embodiments, the approaches herein can be used for stent selection. In some embodiments, the approaches herein can be used for surgical planning, which can include robotic surgical planning. In some embodiments, the approaches herein can be used for image normalization. In some embodiments, the approaches herein can be used for identifying plaque calcification thresholds. In some embodiments, the approaches herein can be used for identifying thin cap fibroatheroma. In some embodiments, the approaches herein can be used for coronary artery tree reconstruction. Some embodiments are directed to coronary artery disease risk stratification.

IPC Classes  ?

• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/46 - Arrangements for interfacing with the operator or the patient
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/46 - Arrangements for interfacing with the operator or the patient
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

This application is directed to systems, methods, and devices for image based analysis of plaque. In some embodiments, the approaches herein can be used for developing treatment plans, which can include local treatment, systemic treatment, or both. In some embodiments, the approaches herein can be used for stent selection. In some embodiments, the approaches herein can be used for surgical planning, which can include robotic surgical planning. In some embodiments, the approaches herein can be used for image normalization. In some embodiments, the approaches herein can be used for identifying plaque calcification thresholds. In some embodiments, the approaches herein can be used for identifying thin cap fibroatheroma. In some embodiments, the approaches herein can be used for coronary artery tree reconstruction. Some embodiments are directed to coronary artery disease risk stratification.

IPC Classes  ?

• G06T 7/00 - Image analysis
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/02 - Arrangements for diagnosis sequentially in different planesStereoscopic radiation diagnosis
• A61B 6/03 - Computed tomography [CT]
• A61B 6/42 - Arrangements for detecting radiation specially adapted for radiation diagnosis
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 5/60 - Image enhancement or restoration using machine learning, e.g. neural networks
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/766 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using regression, e.g. by projecting features on hyperplanes
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/46 - Arrangements for interfacing with the operator or the patient
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• G06V 40/14 - Vascular patterns
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/04 - Positioning of patientsTiltable beds or the like
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 40/14 - Vascular patterns

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• G06T 7/00 - Image analysis
• G06T 7/10 - SegmentationEdge detection
• G06T 7/60 - Analysis of geometric attributes
• G06V 20/50 - Context or environment of the image
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• G06T 7/00 - Image analysis
• G06T 7/10 - SegmentationEdge detection
• G06T 7/60 - Analysis of geometric attributes
• G06V 20/50 - Context or environment of the image
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• G06T 7/00 - Image analysis
• G06T 7/10 - SegmentationEdge detection
• G06T 7/60 - Analysis of geometric attributes
• G06V 20/50 - Context or environment of the image
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• G06T 7/00 - Image analysis
• G06T 7/10 - SegmentationEdge detection
• G06T 7/60 - Analysis of geometric attributes
• G06V 20/50 - Context or environment of the image
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, perform computational fluid dynamics analysis, facilitate assessment of risk of heart disease and coronary artery disease, enhance drug development, determine a CAD risk factor goal, provide atherosclerosis and vascular morphology characterization, and determine indication of myocardial risk, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• G06T 7/00 - Image analysis
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• G06T 7/00 - Image analysis
• G06T 7/10 - SegmentationEdge detection
• G06T 7/60 - Analysis of geometric attributes
• G06V 20/50 - Context or environment of the image
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• G06T 7/00 - Image analysis
• G06T 7/10 - SegmentationEdge detection
• G06T 7/60 - Analysis of geometric attributes
• G06V 20/50 - Context or environment of the image
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/46 - Arrangements for interfacing with the operator or the patient
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• G06T 7/00 - Image analysis
• G06T 7/10 - SegmentationEdge detection
• G06T 7/60 - Analysis of geometric attributes
• G06V 20/50 - Context or environment of the image
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• G06T 7/00 - Image analysis
• G06T 7/10 - SegmentationEdge detection
• G06T 7/60 - Analysis of geometric attributes
• G06V 20/50 - Context or environment of the image
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• G06T 7/00 - Image analysis
• G06T 7/10 - SegmentationEdge detection
• G06T 7/60 - Analysis of geometric attributes
• G06V 20/50 - Context or environment of the image
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• G06T 7/00 - Image analysis
• G06T 7/10 - SegmentationEdge detection
• G06T 7/60 - Analysis of geometric attributes
• G06V 20/50 - Context or environment of the image
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• G06T 7/00 - Image analysis
• G06T 7/10 - SegmentationEdge detection
• G06T 7/60 - Analysis of geometric attributes
• G06V 20/50 - Context or environment of the image
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 40/14 - Vascular patterns

Abstract

Systems and methods of facilitating determination of risk of coronary artery disease (CAD) based at least in part on one or more measurements derived from non-invasive medical image analysis. The methods can include accessing a non-invasive generated medical image, identifying one or more arteries, identifying, regions of plaque within an artery, analyzing the regions of plaque to identify low density non-calcified plaque, non-calcified plaque, or calcified plaque based at least in part on density, determining a distance from identified regions of low density non-calcified plaque to one or more of a lumen wall or vessel wall, determining embeddedness of the regions of low density non-calcified plaque by one or more of non-calcified plaque or calcified plaque, determining a shape of the more regions of low density non-calcified plaque, and generating a display of the analysis to facilitate determination of one or more of a risk of CAD of the subject.

IPC Classes  ?

• G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• G06T 7/00 - Image analysis
• G06T 7/10 - SegmentationEdge detection
• G06T 7/60 - Analysis of geometric attributes
• G06V 20/50 - Context or environment of the image
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• G06V 10/22 - Image preprocessing by selection of a specific region containing or referencing a patternLocating or processing of specific regions to guide the detection or recognition
• G06V 10/26 - Segmentation of patterns in the image fieldCutting or merging of image elements to establish the pattern region, e.g. clustering-based techniquesDetection of occlusion
• G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, perform computational fluid dynamics analysis, facilitate assessment of risk of heart disease and coronary artery disease, enhance drug development, determine a CAD risk factor goal, provide atherosclerosis and vascular morphology characterization, and determine indication of myocardial risk, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• G06T 7/00 - Image analysis
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations

Abstract

Various embodiments described herein relate to systems, devices, and methods for non-invasive image-based plaque analysis and risk determination. In particular, in some embodiments, the systems, devices, and methods described herein are related to analysis of one or more regions of plaque, such as for example coronary plaque, using non-invasively obtained images that can be analyzed using computer vision or machine learning to identify, diagnose, characterize, treat and/or track coronary artery disease.

IPC Classes  ?

• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons

Goods & Services

Software as a service (SAAS) services featuring software for generating cardiovascular analysis based on medical images; software as a service (SAAS) services featuring software for generating cardiovascular analysis based on medical images and machine learning; cardiovascular medical image processing software design; updating of cardiovascular medical image processing software; software as a service (SAAS) services featuring software for controlling and managing cardiovascular analyses; computer software design; computer software development; software design and development; software as a service (SAAS) services featuring software for cardiovascular imaging, namely, for interpreting the results of cardiovascular medical imaging scans; computer software design, computer programming, and maintenance of computer software; software as a service (SAAS) services featuring software for cardiovascular imaging, namely, for interpreting the results of cardiovascular medical imaging scans based on machine learning; Image-based cardiovascular analysis services for medical diagnostic and treatment purposes; cardiovascular analysis testing, monitoring, and reporting services for medical diagnostic and treatment purposes; cardiovascular analysis for diagnostic or treatment purposes; cardiovascular image analysis services for medical diagnostic and treatment purposes; cardiovascular medical information; cardiovascular medical screening; cardiovascular medical advisory services; providing cardiovascular medical information

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/46 - Arrangements for interfacing with the operator or the patient
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06T 7/00 - Image analysis
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

A method for characterization of coronary plaque tissue data and perivascular tissue data using image data gathered from a computed tomography (CT) scan along a blood vessel, the image information including radiodensity values of coronary plaque and perivascular tissue located adjacent to the coronary plaque, the method comprising quantifying radiodensity in regions of coronary plaque, quantifying, radiodensity in at least one region of corresponding perivascular tissue adjacent to the coronary plaque, determining gradients of the quantified radiodensity values within the coronary plaque and the quantified radiodensity values within the corresponding perivascular tissue, and determining a ratio of the quantified radiodensity values within the coronary plaque and the corresponding perivascular tissue; and characterizing the coronary plaque by analyzing a gradient of the quantified radiodensity values in the coronary plaque and the corresponding perivascular, and/or the ratio of the coronary plaque radiodensity values and the radiodensity values of the corresponding perivascular tissue.

IPC Classes  ?

• A61B 6/03 - Computed tomography [CT]
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• G06T 7/00 - Image analysis

Abstract

Systems and methods of facilitating determination of risk of coronary artery disease (CAD) based at least in part on one or more measurements derived from non-invasive medical image analysis. The methods can include accessing a non-invasive generated medical image, identifying one or more arteries, identifying, regions of plaque within an artery, analyzing the regions of plaque to identify low density non-calcified plaque, non-calcified plaque, or calcified plaque based at least in part on density, determining a distance from identified regions of low density non-calcified plaque to one or more of a lumen wall or vessel wall, determining embeddedness of the regions of low density non-calcified plaque by one or more of non-calcified plaque or calcified plaque, determining a shape of the more regions of low density non-calcified plaque, and generating a display of the analysis to facilitate determination of one or more of a risk of CAD of the subject.

IPC Classes  ?

• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons

Abstract

Systems and methods of facilitating determination of risk of coronary artery disease (CAD) based at least in part on one or more measurements derived from non-invasive medical image analysis. The methods can include accessing a non-invasive generated medical image, identifying one or more arteries, identifying, regions of plaque within an artery, analyzing the regions of plaque to identify low density non-calcified plaque, non-calcified plaque, or calcified plaque based at least in part on density, determining a distance from identified regions of low density non-calcified plaque to one or more of a lumen wall or vessel wall, determining embeddedness of the regions of low density non-calcified plaque by one or more of non-calcified plaque or calcified plaque, determining a shape of the more regions of low density non-calcified plaque, and generating a display of the analysis to facilitate determination of one or more of a risk of CAD of the subject.

IPC Classes  ?

• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons

Abstract

Systems and methods of facilitating determination of risk of coronary artery disease (CAD) based at least in part on one or more measurements derived from non-invasive medical image analysis. The methods can include accessing a non-invasive generated medical image, identifying one or more arteries, identifying, regions of plaque within an artery, analyzing the regions of plaque to identify low density non-calcified plaque, non-calcified plaque, or calcified plaque based at least in part on density, determining a distance from identified regions of low density non-calcified plaque to one or more of a lumen wall or vessel wall, determining embeddedness of the regions of low density non-calcified plaque by one or more of non-calcified plaque or calcified plaque, determining a shape of the more regions of low density non-calcified plaque, and generating a display of the analysis to facilitate determination of one or more of a risk of CAD of the subject.

IPC Classes  ?

• G06T 7/00 - Image analysis
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume

Abstract

Systems and methods of facilitating determination of risk of coronary artery disease (CAD) based at least in part on one or more measurements derived from non-invasive medical image analysis. The methods can include accessing a non-invasive generated medical image, identifying one or more arteries, identifying, regions of plaque within an artery, analyzing the regions of plaque to identify low density non-calcified plaque, non-calcified plaque, or calcified plaque based at least in part on density, determining a distance from identified regions of low density non-calcified plaque to one or more of a lumen wall or vessel wall, determining embeddedness of the regions of low density non-calcified plaque by one or more of non-calcified plaque or calcified plaque, determining a shape of the more regions of low density non-calcified plaque, and generating a display of the analysis to facilitate determination of one or more of a risk of CAD of the subject.

IPC Classes  ?

• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• G06T 7/00 - Image analysis

Abstract

Systems and methods of facilitating determination of risk of coronary artery disease (CAD) based at least in part on one or more measurements derived from non-invasive medical image analysis. The methods can include accessing a non-invasive generated medical image, identifying one or more arteries, identifying, regions of plaque within an artery, analyzing the regions of plaque to identify low density non-calcified plaque, non-calcified plaque, or calcified plaque based at least in part on density, determining a distance from identified regions of low density non-calcified plaque to one or more of a lumen wall or vessel wall, determining embeddedness of the regions of low density non-calcified plaque by one or more of non-calcified plaque or calcified plaque, determining a shape of the more regions of low density non-calcified plaque, and generating a display of the analysis to facilitate determination of one or more of a risk of CAD of the subject.

IPC Classes  ?

• G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
• G06T 7/00 - Image analysis
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume

Abstract

Systems and methods of facilitating determination of risk of coronary artery disease (CAD) based at least in part on one or more measurements derived from non-invasive medical image analysis. The methods can include accessing a non-invasive generated medical image, identifying one or more arteries, identifying, regions of plaque within an artery, analyzing the regions of plaque to identify low density non-calcified plaque, non-calcified plaque, or calcified plaque based at least in part on density, determining a distance from identified regions of low density non-calcified plaque to one or more of a lumen wall or vessel wall, determining embeddedness of the regions of low density non-calcified plaque by one or more of non-calcified plaque or calcified plaque, determining a shape of the more regions of low density non-calcified plaque, and generating a display of the analysis to facilitate determination of one or more of a risk of CAD of the subject.

IPC Classes  ?

• G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume

Abstract

Systems and methods of facilitating determination of risk of coronary artery disease (CAD) based at least in part on one or more measurements derived from non-invasive medical image analysis. The methods can include accessing a non-invasive generated medical image, identifying one or more arteries, identifying, regions of plaque within an artery, analyzing the regions of plaque to identify low density non-calcified plaque, non-calcified plaque, or calcified plaque based at least in part on density, determining a distance from identified regions of low density non-calcified plaque to one or more of a lumen wall or vessel wall, determining embeddedness of the regions of low density non-calcified plaque by one or more of non-calcified plaque or calcified plaque, determining a shape of the more regions of low density non-calcified plaque, and generating a display of the analysis to facilitate determination of one or more of a risk of CAD of the subject.

IPC Classes  ?

• G06T 7/12 - Edge-based segmentation
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• G06T 7/00 - Image analysis
• G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume

Abstract

Systems and methods of facilitating determination of risk of coronary artery disease (CAD) based at least in part on one or more measurements derived from non-invasive medical image analysis. The methods can include accessing a non-invasive generated medical image, identifying one or more arteries, identifying, regions of plaque within an artery, analyzing the regions of plaque to identify low density non-calcified plaque, non-calcified plaque, or calcified plaque based at least in part on density, determining a distance from identified regions of low density non-calcified plaque to one or more of a lumen wall or vessel wall, determining embeddedness of the regions of low density non-calcified plaque by one or more of non-calcified plaque or calcified plaque, determining a shape of the more regions of low density non-calcified plaque, and generating a display of the analysis to facilitate determination of one or more of a risk of CAD of the subject.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 8/08 - Clinical applications
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06T 7/00 - Image analysis

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, perform computational fluid dynamics analysis, facilitate assessment of risk of heart disease and coronary artery disease, enhance drug development, determine a CAD risk factor goal, provide atherosclerosis and vascular morphology characterization, and determine indication of myocardial risk, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• G06T 7/00 - Image analysis
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations

Goods & Services

Software as a service (SAAS) services featuring software for generating cardiovascular analysis based on medical images; software as a service (SAAS) services featuring software for generating cardiovascular analysis based on medical images and machine learning; cardiovascular medical image processing software design; updating of cardiovascular medical image processing software; software as a service (SAAS) services featuring software for controlling and managing cardiovascular analyses; computer software design; computer software development; software design and development; software as a service (SAAS) services featuring software for cardiovascular imaging, namely, for interpreting the results of cardiovascular medical imaging scans; computer software design, computer programming, and maintenance of computer software; software as a service (SAAS) services featuring software for cardiovascular imaging, namely, for interpreting the results of cardiovascular medical imaging scans based on machine learning; Web-based cardiovascular analysis services of images for medical diagnostic and treatment purposes; cardiovascular analysis testing, monitoring, and reporting services; cardiovascular analysis for diagnostic or treatment purposes; cardiovascular image analysis services; cardiovascular medical information; cardiovascular medical screening; cardiovascular medical advisory services; providing cardiovascular medical information

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 8/14 - Echo-tomography
• A61B 6/03 - Computed tomography [CT]
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• G06T 7/00 - Image analysis
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61K 49/04 - X-ray contrast preparations
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• G06F 18/10 - Pre-processingData cleansing
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 40/14 - Vascular patterns

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, perform computational fluid dynamics analysis, facilitate assessment of risk of heart disease and coronary artery disease, enhance drug development, determine a CAD risk factor goal, provide atherosclerosis and vascular morphology characterization, and determine indication of myocardial risk, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• G06T 7/00 - Image analysis
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• G06T 7/00 - Image analysis
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/03 - Computed tomography [CT]
• A61B 8/14 - Echo-tomography
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, perform computational fluid dynamics analysis, facilitate assessment of risk of heart disease and coronary artery disease, enhance drug development, determine a CAD risk factor goal, provide atherosclerosis and vascular morphology characterization, and determine indication of myocardial risk, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• G06T 7/00 - Image analysis
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 6/50 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body partsApparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific clinical applications
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 8/14 - Echo-tomography
• A61K 49/04 - X-ray contrast preparations

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• G06T 7/00 - Image analysis
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/03 - Computed tomography [CT]
• A61B 8/14 - Echo-tomography
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• G06T 7/00 - Image analysis
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/03 - Computed tomography [CT]
• A61B 8/14 - Echo-tomography
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• G06T 7/00 - Image analysis
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/03 - Computed tomography [CT]
• A61B 8/14 - Echo-tomography
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, perform computational fluid dynamics analysis, facilitate assessment of risk of heart disease and coronary artery disease, enhance drug development, determine a CAD risk factor goal, provide atherosclerosis and vascular morphology characterization, and determine indication of myocardial risk, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• G06T 7/00 - Image analysis
• A61B 8/14 - Echo-tomography
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing

Abstract

A method for characterization of coronary plaque tissue data and perivascular tissue data using image data gathered from a computed tomography (CT) scan along a blood vessel, the image information including radiodensity values of coronary plaque and perivascular tissue located adjacent to the coronary plaque, the method comprising quantifying radiodensity in regions of coronary plaque, quantifying, radiodensity in at least one region of corresponding perivascular tissue adjacent to the coronary plaque, determining gradients of the quantified radiodensity values within the coronary plaque and the quantified radiodensity values within the corresponding perivascular tissue, and determining a ratio of the quantified radiodensity values within the coronary plaque and the corresponding perivascular tissue; and characterizing the coronary plaque by analyzing a gradient of the quantified radiodensity values in the coronary plaque and the corresponding perivascular, and/or the ratio of the coronary plaque radiodensity values and the radiodensity values of the corresponding perivascular tissue.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• G06T 7/00 - Image analysis

Abstract

A method for characterization of coronary plaque tissue data and perivascular tissue data using image data gathered from a computed tomography (CT) scan along a blood vessel, the image information including radiodensity values of coronary plaque and perivascular tissue located adjacent to the coronary plaque, the method comprising quantifying radiodensity in regions of coronary plaque, quantifying, radiodensity in at least one region of corresponding perivascular tissue adjacent to the coronary plaque, determining gradients of the quantified radiodensity values within the coronary plaque and the quantified radiodensity values within the corresponding perivascular tissue, and determining a ratio of the quantified radiodensity values within the coronary plaque and the corresponding perivascular tissue; and characterizing the coronary plaque by analyzing a gradient of the quantified radiodensity values in the coronary plaque and the corresponding perivascular, and/or the ratio of the coronary plaque radiodensity values and the radiodensity values of the corresponding perivascular tissue.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• G06T 7/00 - Image analysis

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• G06T 7/00 - Image analysis
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61B 6/03 - Computed tomography [CT]
• A61B 8/14 - Echo-tomography
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, perform computational fluid dynamics analysis, facilitate assessment of risk of heart disease and coronary artery disease, enhance drug development, determine a CAD risk factor goal, provide atherosclerosis and vascular morphology characterization, and determine indication of myocardial risk, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• G06T 7/00 - Image analysis
• A61B 8/14 - Echo-tomography
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 6/03 - Computed tomography [CT]
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61K 49/04 - X-ray contrast preparations
• G06F 18/10 - Pre-processingData cleansing

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 8/14 - Echo-tomography
• A61B 6/03 - Computed tomography [CT]
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• G06T 7/00 - Image analysis
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61K 49/04 - X-ray contrast preparations
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• G06F 18/10 - Pre-processingData cleansing
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 40/14 - Vascular patterns

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 8/14 - Echo-tomography
• A61B 6/03 - Computed tomography [CT]
• A61B 5/00 - Measuring for diagnostic purposes Identification of persons
• G06T 7/00 - Image analysis
• A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
• A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fieldsMeasuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
• A61K 49/04 - X-ray contrast preparations
• A61B 5/02 - Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
• G06F 18/10 - Pre-processingData cleansing
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
• G06V 10/20 - Image preprocessing
• G06V 10/24 - Aligning, centring, orientation detection or correction of the image
• G06V 40/14 - Vascular patterns

Goods & Services

Providing online non-downloadable software for generating cardiovascular diagnostics and predictions based on medical images for use in the fields of heart disease, cardiology, and cardiovascular medicine via a website; providing temporary use of online non-downloadable software for generating cardiovascular diagnostics and predictions based on medical images for use in the fields of heart disease, cardiology, and cardiovascular medicine; providing quality assurance services in the fields of heart disease, cardiology, and cardiovascular medicine. Medical and medical clinical services in the fields of heart disease, cardiology, and cardiovascular medicine; providing information in the fields of heart disease, cardiology, and cardiovascular medicine via a website; providing information in the fields of heart disease, cardiology, and cardiovascular medicine.

Abstract

The disclosure herein relates to systems, methods, and devices for medical image analysis, diagnosis, risk stratification, decision making and/or disease tracking. In some embodiments, the systems, devices, and methods described herein are configured to analyze non-invasive medical images of a subject to automatically and/or dynamically identify one or more features, such as plaque and vessels, and/or derive one or more quantified plaque parameters, such as radiodensity, radiodensity composition, volume, radiodensity heterogeneity, geometry, location, perform computational fluid dynamics analysis, facilitate assessment of risk of heart disease and coronary artery disease, enhance drug development, determine a CAD risk factor goal, provide atherosclerosis and vascular morphology characterization, and determine indication of myocardial risk, and/or the like. In some embodiments, the systems, devices, and methods described herein are further configured to generate one or more assessments of plaque-based diseases from raw medical images using one or more of the identified features and/or quantified parameters.

IPC Classes  ?

• G06T 7/00 - Image analysis
• A61B 6/00 - Apparatus or devices for radiation diagnosisApparatus or devices for radiation diagnosis combined with radiation therapy equipment
• A61B 8/08 - Clinical applications
• A61B 6/03 - Computed tomography [CT]