Provided is a method for performing a prediction work on a target image, including dividing the target image into a plurality of sub-images, generating prediction results for a plurality of pixels included in each of the plurality of divided sub-images, applying weights to the prediction results for the plurality of pixels, and merging the prediction results for the plurality of pixels applied with the weights.
G06F 18/2415 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate
The present disclosure relates to a method, performed by at least one computing device, for predicting a response to an immune checkpoint inhibitor. The method includes receiving a first pathology slide image, detecting one or more target items in the first pathology slide image, determining at least one of an immune phenotype of at least some regions in the first pathology slide image or information associated with the immune phenotype based on the detection result for the one or more target items, and generating a prediction result as to whether or not a patient associated with the first pathology slide image responds to the immune checkpoint inhibitor, based on the immune phenotype of the at least some regions in the first pathology slide image or the information associated with the immune phenotype.
44 - Medical, veterinary, hygienic and cosmetic services; agriculture, horticulture and forestry services
Goods & Services
Medical analysis services for cancer diagnosis and prognosis; providing information in the field of cancer prevention, screening, diagnosis and treatment; medical analysis for the diagnosis and treatment of persons; providing cancer screening services; medical diagnostic services; medical examination of individuals (Provision of reports relating to the -); medical analysis services; telemedicine services; medical information; medical examinations.
44 - Medical, veterinary, hygienic and cosmetic services; agriculture, horticulture and forestry services
Goods & Services
medical analysis services for cancer diagnosis and prognosis; providing information in the field of cancer prevention, screening, diagnosis and treatment; medical analysis for the diagnosis and treatment of persons; providing cancer screening services; medical diagnostic services; medical examination of individuals (Provision of reports relating to the -); medical analysis services; telemedicine services; medical information; medical examinations.
44 - Medical, veterinary, hygienic and cosmetic services; agriculture, horticulture and forestry services
Goods & Services
medical analysis services for cancer diagnosis and prognosis; providing information in the field of cancer prevention, screening, diagnosis and treatment; medical analysis for the diagnosis and treatment of persons; providing cancer screening services; medical diagnostic services; medical examination of individuals (Provision of reports relating to the -); medical analysis services; telemedicine services; medical information; medical examinations.
A radiology report generation system is configured to obtain an analysis result for a target medical image using an artificial intelligence analysis model, extract at least one similar image to the target medical image from a catalog set comprising medical image-radiology report pairs; determine at least one radiology report paired with the at least one similar image as a reference image, and generate a radiology report for the target medical image based on the analysis result, using the reference report as a guideline.
The present disclosure relates to a radiology report generation system and method. This radiology report generation system is configured to: obtain an analysis result for a target medical image by using an artificial intelligence analysis model; extract at least one similar image to the target medical image from a catalog set composed of pairs of medical images and radiology reports; determine at least one radiology report corresponding to the at least one similar image as a reference report; and generate a radiology report from the analysis result for the target medical image by using the reference report as a guideline.
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
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
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 10/20 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
A method for operating a medical imaging device includes obtaining lesion information on at least one lesion detected from a medical image, determining a shape and a position of at least one contour corresponding to the at least one lesion based on the obtained lesion information, determining a position of at least one text region that includes a text indicating the lesion information on the at least one lesion in the medical image, and displaying the at least one contour and the text included in the at least one text region on the medical image, based on the determined shape and position of the at least one contour and the determined position of the at least one text region.
G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]Salient regional features
G06T 7/70 - Determining position or orientation of objects or cameras
G06T 11/20 - Drawing from basic elements, e.g. lines or circles
G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
9.
METHOD AND DEVICE FOR PREDICTING CANCER TREATMENT RESPONSE TO IMMUNE CHECKPOINT INHIBITOR
Provided is a method or a device for predicting a cancer treatment response to an immune checkpoint inhibitor, wherein the method, according to an aspect of the present disclosure, enables accurate prediction of the treatment response of a cancer patient to an immune checkpoint inhibitor and facilitates the selection of an appropriate treatment strategy.
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 30/00 - ICT specially adapted for the handling or processing of medical images
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
C12Q 1/6881 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for tissue or cell typing, e.g. human leukocyte antigen [HLA] probes
A computing device includes a memory storing at least one program, and a processor configured to perform at least one operation by executing the at least one program, wherein the processor is configured to generate virtual data including information about survival rates of virtual patients included in a first group, based on pre-generated survival data, generate control group data by classifying each of the virtual patients as a responder or a non-responder according to a certain criterion, generate experimental group data based on at least one of medical images and survival data of actual patients included in a second group to which a specific regime has been applied, and output a result of comparison between the control group data and the experimental group data.
G16H 10/20 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
11.
METHOD AND SYSTEM FOR PREDICTING EXPRESSION OF BIOMARKER FROM MEDICAL IMAGE
The present disclosure relates to a method for predicting biomarker expression from a medical image. The method for predicting biomarker expression includes receiving a medical image. and outputting indices of biomarker expression for the at least one lesion included in the medical image by using a first machine learning model.
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
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
12.
METHOD AND SYSTEM FOR DETERMINING ABNORMALITY IN MEDICAL DEVICE
A method for determining an abnormality in a medical device from a medical image is provided. The method for determining an abnormality in a medical device comprises receiving a medical image, and detecting information on at least a part of a target medical device included in the received medical image.
A computing apparatus includes a memory storing at least one program and a processor configured to perform at least one operation by executing the at least one program, wherein the processor is further configured to analyze a pathological slide image to classify at least one of cells and tissues included in the pathological slide image into at least one type, segment the pathological slide image into subpatches on the basis of a result of the classification, and analyze the subpatches to output information regarding components of a cell included in each of the subpatches.
G06V 10/28 - Quantising the image, e.g. histogram thresholding for discrimination between background and foreground patterns
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 10/86 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using syntactic or structural representations of the image or video pattern, e.g. symbolic string recognitionArrangements for image or video recognition or understanding using pattern recognition or machine learning using graph matching
14.
METHOD AND APPARATUS FOR CUSTOMIZING MACHINE LEARNING MODEL FOR MEDICAL IMAGE ANALYSIS
A computing device according to one aspect of the present invention comprises: a memory in which at least one program is stored; and a processor for performing at least one operation by executing the at least one program, wherein the processor acquires a pre-trained machine learning model generated at a first site, retrains the pre-trained machine learning model on the basis of information related to medical data collected at a second site, evaluates the performance of the retrained machine learning model, and applies the retrained machine learning model on the basis of the evaluation result.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
15.
METHOD AND SYSTEM FOR GENERATING MEDICAL PREDICTION RELATED TO BIOMARKER FROM MEDICAL DATA
A method for generating a medical prediction related to a biomarker from medical data is provided, which includes obtaining medical data associated with a patient, determining a region of interest in the medical data, extracting one or more features associated with the medical data based on the region of interest, and generating a medical prediction for the patient based on the extracted one or more features.
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
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
16.
METHOD AND SYSTEM FOR ARTIFICIAL INTELLIGENCE-BASED MEDICAL IMAGE ANALYSIS
An image analysis device includes a memory and a processor configured to execute instructions stored in the memory, wherein the processor is configured to detect an indeterminate region or an abnormal region from an input medical image using an artificial intelligence (AI) model trained to detect a suspicious region and a lesion region in medical images and determine the input medical image as a normal case when the indeterminate region or the abnormal region is not detected in the input medical image.
A method for parallel processing a digitally scanned pathology image is performed by a plurality of processors and includes performing, by a first processor, a first operation of generating a first batch from a first set of patches extracted from a digitally scanned pathology image and providing the generated first batch to a second processor, performing, by the first processor, a second operation of generating a second batch from a second set of patches extracted from the digitally scanned pathology image and providing the generated second batch to the second processor, and performing, by the second processor, a third operation of outputting a first analysis result from the first batch by using a machine learning model, with at least part of time frame for the second operation performed by the first processor overlapping at least part of time frame for the third operation performed by the second processor.
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 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 70/60 - ICT specially adapted for the handling or processing of medical references relating to pathologies
18.
METHOD AND APPARATUS FOR OUTPUTTING INFORMATION RELATED TO A PATHOLOGICAL SLIDE IMAGE
A computing apparatus includes: at least one memory; and at least one processor, wherein the processor generates quantitative information regarding at least one cell included in a region of interest of a pathological slide image by analyzing the pathological slide image, generates qualitative information regarding at least one tissue included in the pathological slide image by analyzing the pathological slide image, and controls a display apparatus to output at least one of the quantitative information and the qualitative information on the pathological slide image according to a manipulation of a user.
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
19.
METHOD FOR MANAGING ANNOTATION JOB, APPARATUS AND SYSTEM SUPPORTING THE SAME
A computing device obtains information about a medical slide image, and determines a dataset type of the medical slide image and a panel of the medical slide image. The computing device assigns to an annotator account, an annotation job defined by at least the medical slide image, the determined dataset type, an annotation task, and a patch that is a partial area of the medical slide image. The annotation task includes the determined panel, and the panel is designated as one of a plurality of panels including a cell panel, a tissue panel, and a structure panel. The dataset type indicates a use of the medical slide image and is designated as one of a plurality of uses including a training use of a medical learning model and a validation use of the machine learning model.
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 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
G06V 10/778 - Active pattern-learning, e.g. online learning of image or video features
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
20.
APPARATUS FOR QUALITY MANAGEMENT OF MEDICAL IMAGE INTERPRETATION USING MACHINE LEARNING, AND METHOD THEREOF
Provided are a computerized image interpretation method and a device for analyzing a medical image. The image interpretation method may include receiving, at a processor, a medical image, and receiving report information including a healthcare worker's judgement result of the medical image. The method may also include generating, at the processor, result information representing correspondence between first lesion information, which is related to a lesion in the medical image acquired on the basis of the medical image, and second lesion information, which is related to a lesion in the medical image acquired on the basis of the report information, by applying the first lesion information and the second lesion information to a third analysis model. The method may further include outputting, at the processor, the result information.
09 - Scientific and electric apparatus and instruments
38 - Telecommunications services
42 - Scientific, technological and industrial services, research and design
44 - Medical, veterinary, hygienic and cosmetic services; agriculture, horticulture and forestry services
Goods & Services
Software as a medical device (SaMD), downloadable; computer software for making electronic charts, for medical purposes; computer software for diagnosing diseases for medical purposes; computer software for use in medical decision support systems; software for processing digital images; downloadable database management software applications; computer software for data and document capture, transmission, storage and indexing; data processing software; computer software to enhance the audio-visual capabilities of multimedia applications, namely, for the integration of text, audio, graphics, still images and moving pictures; downloadable computer software for collecting, analyzing and organizing data in the field of deep learning Provision of access to medical information via the internet; providing access to databases; transmission and reception of information and data via telecommunication networks; transmission of data/sound or images; providing the transmission of information via on-line network; providing access to information via website; transmission and reception of database information via the wired or wireless telecommunication network; providing access to web sites on the internet; providing access to information on the internet; transmission of information via the internet Computer services for the analysis of data; providing temporary use of online non-downloadable computer software for collecting, analyzing and organizing data in the field of deep learning; maintenance and consultancy services relating to software for use in management assistance services for medical image data; development of computer software for use with medical equipment; providing computer software technical support services in the field of medical diagnostics; computer programming services for remote data management of medical diagnostic instruments; software as a service (SaaS); platform as a Service (PaaS); scientific research for medical purposes in the area of cancerous diseases; medical research laboratory services for predicting disease Medical and health care services; medical consultations; medical information; providing information in the field of medicine; medical information services provided via the Internet; medical examinations; breast cancer screening services; providing cancer screening services; medical analysis services for cancer diagnosis and prognosis; providing information in the field of cancer prevention, screening, diagnosis and treatment
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable computer software to automate data warehousing; Downloadable computer software for application and database integration; downloadable computer software for searching and retrieving information across a computer network; image analysis devices, namely, computers, image intensifiers, computer display monitors, video cameras, image sensors, and computer network server all for analyzing and interpreting medical images for use in the medical field; downloadable computer software for the diagnosis of cancer; Software as a medical device (SaMD), downloadable, for assisting in the detection of cancer and diseases based on the medical images; downloadable computer software for making electronic charts, for medical purposes; downloadable computer software for diagnosing diseases for medical purposes; downloadable computer software for use in medical decision support systems; downloadable computer software for processing digital images; downloadable database management software applications for use in cancer diagnosis related healthcare; downloadable computer software for data and document capture, transmission, storage and indexing; downloadable data processing software; downloadable computer software to enhance the audio-visual capabilities of multimedia applications, namely, for the integration of text, audio, graphics, still images and moving pictures; downloadable computer software for collecting, analyzing and organizing data in the field of deep learning. Research relating to data processing; computer programming in the medical field; research and development of medical apparatus and instruments for others; scientific research for medical purposes in the field of cancerous diseases; design of medical diagnostic apparatus and instruments; research and development of medical equipment; computer programming services for remote management of medical diagnostic systems; medical research laboratory services for predicting disease; medical research; computer software development; computer programming services for the analysis of data; providing temporary use of online non- downloadable computer software for collecting, analyzing and organizing data in the field of deep learning; maintenance and consultancy services relating to software for use in management assistance services for medical image data; development of computer software for use with medical equipment; providing computer software technical support services in the field of medical diagnostics; computer programming services for remote data management of medical diagnostic instruments; software as a service (SaaS) services featuring software for medical image analysis, disease detection, clinical decision support and providing diagnostic results to healthcare providers and patients; platform as a Service (PaaS) featuring computer software platforms for medical image and data analysis, healthcare data management and clinical decision support; scientific research for medical purposes in the area of cancerous diseases.
23.
METHOD AND SYSTEM FOR ANALYZING PATHOLOGICAL IMAGE
The present disclosure relates to a method, performed by at least one processor of an information processing system, of analyzing a pathological image. The method includes receiving a pathological image, detecting an object associated with medical information, in the received pathological image by using a machine learning model, generating an analysis result on the received pathological image, based on a result of the detecting, and outputting medical information about at least one region included in the pathological image, based on the analysis result.
A computing device includes: at least one memory; and at least one processor, wherein the at least one processor is configured to obtain information related to tissues or cells represented in a pathological slide image by analyzing the pathological slide image, predict a ratio of circulating tumor deoxyribonucleic acid (DNA) to cell free DNA, based on the information, and generate guidance related to a follow-up examination, based on the ratio.
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
Provided is a method for analysing a pathology image, which is performed by at least one processor and includes acquiring a pathology image, inputting the acquired pathology image into a machine learning model and acquiring an analysis result for the pathology image from the machine learning model, and outputting the acquired analysis result, in which the machine learning model is a model trained by using a training data set generated based on a first pathology data set associated with a first domain and a second pathology data set associated with a second domain different from the first domain.
G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts
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 10/98 - Detection or correction of errors, e.g. by rescanning the pattern or by human interventionEvaluation of the quality of the acquired patterns
26.
METHOD AND APPARATUS FOR ANALYZING PATHOLOGICAL SLIDE IMAGE
A computing device includes at least one memory and at least one processor. The at least one processor is configured to detect a plurality of tumor cells included in one or more tumor areas (cancer areas) from a pathological slide image, determine a cell expression class of the plurality of tumor cells, based on a biomarker expression degree of the plurality of tumor cells, and generate a heatmap image for the pathological slide image, based on a result of the determining.
The present disclosure relates to a medical image analysis method using a processor and a memory which are hardware. The method includes generating predicted second metadata for a medical image by using a prediction model, and determining a processing method of the medical image based on one of first metadata stored corresponding to the medical image and the second metadata.
G06T 7/70 - Determining position or orientation of objects or cameras
G06V 10/70 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning
G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
The present disclosure relates to a method for predicting biomarker expression from a medical image. The method for predicting biomarker expression includes receiving a medical image, and outputting indices of biomarker expression for the at least one lesion included in the medical image by using a first machine learning model.
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
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
29.
METHOD AND DEVICE FOR ANALYZING PATHOLOGY SLIDE IMAGE
A computing device according to one aspect comprises: at least one memory; and at least one processor, wherein the at least one processor identifies at least one tertiary lymphoid structure (TLS) from a pathology slide image, generates information related to the at least one tertiary lymphoid structure, and predicts treatment responsiveness of a lesion associated with the pathology slide image on the basis of the information.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 30/00 - ICT specially adapted for the handling or processing of medical images
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]Salient regional features
G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
30.
METHOD AND DEVICE FOR ANALYZING PATHOLOGY SLIDE IMAGE
The computing device according to an aspect comprises: at least one memory; and at least one processor, wherein the at least one processor is configured to: identify at least one tissue region from a pathology slide image by using an artificial intelligence model; generate spatial distribution-related information for the at least one tissue region on the basis of an image arithmetic operation of the at least one tissue region; and calculate an evaluation index associated with treatment responsiveness, on the basis of the spatial distribution-related information.
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
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
G16H 30/00 - ICT specially adapted for the handling or processing of medical images
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
Provided is a method or apparatus for predicting treatment response to an immune checkpoint inhibitor, the method comprising: determining a density of tumor-infiltrating lymphocytes (TILs) for a pathological image at a first time point using a machine learning model; determining a density of TILs for a pathological image at a second time point using the machine learning model; determining a fold change in density of TILs by using the density of TILs for the pathological image at the first time point and the density of TILs for the pathological image at the second time point; and predicting a treatment response to the immune checkpoint inhibitor in a cancer patient based on the fold change in density of the TILs. According to a method of one aspect, the treatment responsiveness to an immune checkpoint inhibitor in cancer patients can be more accurately predicted and a treatment method can be determined.
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
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
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
The present disclosure relates to a method and device for predicting a treatment response to a HER2-targeted therapeutic agent. In an embodiment, a method of more accurately predicting the therapeutic responsiveness of a cancer patient to the HER2-targeted therapeutic agent and treating cancer may be determined.
44 - Medical, veterinary, hygienic and cosmetic services; agriculture, horticulture and forestry services
Goods & Services
Providing access to an electronic exchange of medical records across a nationwide health information network; transmission of sound, video and information; network transmission of sounds, images, signals and data; transmission of sound, video and information from web cams, video cameras or mobile phones, all featuring live or recorded materials; computer aided transmission of information and images; providing multiple-user access to databases in data networks; telecommunications services, namely, electronic transmission of data via a computer network; providing user access to computer databases in data networks; transmission and reception of database information via wired and wireless telecommunication networks; communications by computer terminals; transmission of digital files; transmission and reception of information and data via telecommunication networks; electronic transmission of data, sound or images; providing access to databases; electronic transmission of digital images; electronic transmission of sound, images and other data and information of all kinds via the Internet; electronic transmission of text message and video; electronic transmission of data, namely, transmission of text, photo and video via the smart phone application; electronic transmission of audio and visual content; providing on-line access to databases; information transfer, namely, electronic transmission of data via a computer network Medical reporting services, namely, providing medical information to medical professionals and patients in the form of reports relating to the medical examination of individuals; managed health care services; medical analysis for the diagnosis and treatment of persons; providing information in the field of cancer prevention, screening, diagnosis and treatment; medical analysis services for cancer diagnosis and prognosis; medical analysis services for the diagnosis of cancer; health care services for treating cancer; providing cancer screening services; providing health information via a web site; providing breast cancer screening services; provision of medical information; medical diagnostic testing, monitoring and reporting services; medical services for the diagnosis of conditions of the human body, namely, cancer; remote monitoring services for medical diagnostic devices and systems, namely, remote monitoring of medical data for medical diagnosis and treatment
34.
METHOD AND DEVICE FOR EVALUATING QUALITY OF PATHOLOGICAL SLIDE IMAGE
A computing device includes at least one memory, and at least one processor configured to analyze at least one object expressed in a pathological slide image, evaluate quality of the pathological slide image based on a result of the analyzing, and perform at least one additional operation according to a result of the evaluating.
SEOUL NATIONAL UNIVERSITY HOSPITAL (Republic of Korea)
Inventor
Kim, Min Chul
Park, Chang Min
Hwang, Eui Jin
Abstract
Some embodiments of the present disclosure provide a pneumothorax detection method performed by a computing device. The method may comprise obtaining predicted pneumothorax information, predicted tube information, and a predicted spinal baseline with respect to an input image from a trained pneumothorax prediction model; determining at least one pneumothorax representative position for the predicted pneumothorax information and at least one tube representative position for the predicted tube information, in a prediction image in which the predicted pneumothorax information and the predicted tube information are displayed; dividing the prediction image into a first region and a second region by the predicted spinal baseline; and determining a region in which the at least one pneumothorax representative position and the at least one tube representative position exist among the first region and the second region.
G06T 7/70 - Determining position or orientation of objects or cameras
G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
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
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
36.
APPARATUS AND METHOD FOR INTERLOCKING LESION LOCATIONS BETWEEN A GUIDE IMAGE AND A 3D TOMOSYNTHESIS IMAGES COMPOSED OF A PLURALITY OF 3D IMAGE SLICES
Provided are a method and an apparatus for interlocking a lesion location between a 2D medical image and 3D tomosynthesis images including a plurality of 3D image slices.
The present disclosure relates to a medical image analysis method using a processor and a memory which are hardware. The method includes generating predicted second metadata for a medical image by using a prediction model, and determining a processing method of the medical image based on one of first metadata stored corresponding to the medical image and the second metadata.
Provided is a computing device including at least one memory, and at least one processor configured to obtain feature information corresponding to a pathological slide image, generate medical information associated with the pathological slide image based on the feature information, and output at least one of the medical information and additional information based on the medical information.
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
39.
METHOD AND DEVICE FOR ANALYZING PATHOLOGY SLIDE IMAGE
A computing device according to an aspect comprises: at least one memory; and at least one processor, wherein the processor: divides a pathology slide image into a plurality of patches; for at least one of the plurality of patches, determines whether at least one artifact exists therein; and performs an additional task on the basis of a result of the determination.
A prediction device operated by at least one processor includes: a risk factor inference model implemented with an artificial intelligence model trained to infer risk factors for a disease from input images, configured to receive medical images and output at least one inferred risk factor; and a medical prediction model configured to receive patient information including the at least one inferred risk factor as input and output a medical prediction including a disease risk.
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
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
41.
Method and device for processing pathological slide image
A computing device includes at least one memory, and at least one processor configured to generate, based on first analysis on a pathological slide image, first biomarker expression information, generate, based on a user input for updating at least some of results of the first analysis, second biomarker expression information about the pathological slide image, and control a display device to output a report including medical information about at least some regions included in the pathological slide image, based on at least one of the first biomarker expression information or the second biomarker expression information.
G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
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
42.
METHOD AND APPARATUS FOR ANALYZING PATHOLOGICAL SLIDE IMAGES
A computing apparatus includes at least one memory, and at least one processor, wherein the processor is configured to acquire a pathological slide image showing at least one tissue, generate feature information related to at least one area of the pathological slide image, and detect, from the pathological slide image, at least one cell included in the at least one tissue by using the pathological slide image and the feature information.
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
43.
Method for discriminating suspicious lesion in medical image, method for interpreting medical image, and computing device implementing the methods
A method for interpreting an input image by a computing device operated by at least one processor is provided. The method for interpreting an input image comprises storing an artificial intelligent (AI) model that is trained to classify a lesion detected in the input image as suspicious or non-suspicious and, under a condition of being suspicious, to classify the lesion detected in the input image as malignant or benign-hard representing that the lesion is suspicious but determined to be benign, receiving an analysis target image, by using the AI model, obtaining a classification class of a target lesion detected in the analysis target image and, when the classification class is the suspicious, obtaining at least one of a probability of being suspicious, a probability of being benign-hard, and a probability of malignant for the target lesion, and outputting an interpretation result including at least one probability obtained for the target lesion.
G06V 10/40 - Extraction of image or video features
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
44.
Method and device for processing pathological slide image
A computing device includes at least one memory, and at least one processor configured to generate, based on first analysis on a pathological slide image, first biomarker expression information, generate, based on a user input for updating at least some of results of the first analysis, second biomarker expression information about the pathological slide image, and control a display device to output a report including medical information about at least some regions included in the pathological slide image, based on at least one of the first biomarker expression information or the second biomarker expression information.
G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
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
45.
METHOD AND APPARATUS FOR PROVIDING CONFIDENCE INFORMATION ON RESULT OF ARTIFICIAL INTELLIGENCE MODEL
A computing apparatus operated by at least one processor includes a target artificial intelligence model configured to learn at least one task, and perform a task for an input medical image to output a target result, and a confidence prediction model configured to obtain at least one impact factor that affects the target result based on the input medical image, and estimate confidence information for the target result based on the impact factor.
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
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
46.
METHOD AND SYSTEM FOR PARALLEL PROCESSING FOR MEDICAL IMAGE
There is provided a method for parallel processing a digitally scanned pathology image, in which the method is performed by a plurality of processors and includes performing, by a first processor, a first operation of providing a second processor with a first patch included in the digitally scanned pathology image, performing, by the first processor, a second operation of providing the second processor with a second patch included in the digitally scanned pathology image, and performing, by the second processor, a third operation of outputting a first analysis result from the first patch using a machine learning model, in which at least a part of a time frame for the second operation performed by the first processor may overlap with at least a part of a time frame for the third operation performed by the second processor.
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 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 70/60 - ICT specially adapted for the handling or processing of medical references relating to pathologies
47.
METHOD AND APPARATUS FOR OUTPUTTING INFORMATION RELATED TO A PATHOLOGICAL SLIDE IMAGE
A computing apparatus includes: at least one memory; and at least one processor, wherein the processor generates quantitative information regarding at least one cell included in a region of interest of a pathological slide image by analyzing the pathological slide image, generates qualitative information regarding at least one tissue included in the pathological slide image by analyzing the pathological slide image, and controls a display apparatus to output at least one of the quantitative information and the qualitative information on the pathological slide image according to a manipulation of a user.
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
An image analysis method and an image analysis system are disclosed. The method may include extracting training raw graphic data including at least one first node corresponding to a plurality of histological features of a training tissue slide image, and at least one first edge defined by a relationship between the histological features and generating training graphic data by sampling the first node of the training raw graphic data. The method may also include determining a parameter of a readout function by training a graph neural network (GNN) using the training graphic data and training output data corresponding to the training graphic data, and extracting inference graphic data including at least one second node corresponding to a plurality of histological features of an inference tissue slide image, and at least one second edge decided by a relationship between the histological features of the inference tissue slide 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 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
G06V 10/80 - Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts
49.
METHOD AND SYSTEM FOR PREDICTING RISK OF OCCURRENCE OF LESIONS
A method for predicting a risk of occurrence of a lesion is provided, which is performed by one or more processors and includes acquiring a medical image of a subject, using a machine learning model, predicting a possibility of occurrence of a lesion of the subject from acquired medical image, and outputting a prediction result, in which the machine learning model may be a model trained with a plurality of training medical images and a risk of occurrence of the lesion associated with each training medical image.
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
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
50.
METHOD FOR TRAINING NEURAL NETWORK AND DEVICE THEREOF
Provided is a method for training a neural network and a device thereof. The method for training a neural network with three-dimensional (3D) training image data comprising a plurality of two-dimensional (2D) training image data, comprises: training a first convolutional neural network (CNN) with the plurality of 2D training image data, wherein the first convolutional neural network comprises 2D convolutional layers; and training a second convolutional neural network with the 3D training image data, wherein the second convolutional neural network comprises the 2D convolutional layers and 3D convolutional layers configured to receive an output of the 2D convolutional layers as an input.
G06V 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
G06V 10/77 - Processing image or video features in feature spacesArrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]Blind source separation
G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
Provided is a method for analysing a pathology image, which is performed by at least one processor and includes acquiring a pathology image, inputting the acquired pathology image into a machine learning model and acquiring an analysis result for the pathology image from the machine learning model, and outputting the acquired analysis result, in which the machine learning model is a model trained by using a training data set generated based on a first pathology data set associated with a first domain and a second pathology data set associated with a second domain different from the first domain.
G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts
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 10/98 - Detection or correction of errors, e.g. by rescanning the pattern or by human interventionEvaluation of the quality of the acquired patterns
52.
METHOD AND SYSTEM FOR MEASURING SIZE CHANGE OF TARGET LESION IN X-RAY IMAGE
A method for measuring a size change of a target lesion in an X-ray image is provided, including receiving a first X-ray image including the target lesion and a second X-ray image including the target lesion, calculating an occupancy of a region corresponding to the target lesion in criterion regions in each of the first X-ray image and the second X-ray image, and measuring a size change of the target lesion based on the calculated occupancies.
The present disclosure relates to a method, performed by at least one computing device, for providing information associated with immune phenotype for pathology slide image. The method may include obtaining information associated with immune phenotype for one or more regions of interest (ROIs) in a pathology slide image, generating, based on the information associated with the immune phenotype for one or more ROIs, an image indicative of the information associated with the immune phenotype, and outputting the image indicative of the information associated with immune phenotype.
The present disclosure relates to a method, performed by at least one computing device, for predicting a response to an immune checkpoint inhibitor. The method includes receiving a first pathology slide image, detecting one or more target items in the first pathology slide image, determining at least one of an immune phenotype of at least some regions in the first pathology slide image or information associated with the immune phenotype based on the detection result for the one or more target items, and generating a prediction result as to whether or not a patient associated with the first pathology slide image responds to the immune checkpoint inhibitor, based on the immune phenotype of the at least some regions in the first pathology slide image or the information associated with the immune phenotype.
A computing apparatus includes at least one memory storing at least one program, and at least one processor configured to, by executing the at least one program, acquire at least one of first information regarding a primary clinical trial previously performed on a certain drug and second information indicating an association between the drug and each of candidate biomarkers, set a criterion related to responsitivity to the drug based on the acquired information, and generate information related to a secondary clinical trial based on the set criterion.
G16H 10/20 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
A computing device includes at least one memory, and at least one processor configured to analyze at least one object expressed in a pathological slide image, evaluate quality of the pathological slide image based on a result of the analyzing, and perform at least one additional operation according to a result of the evaluating.
A computing device obtains information about a medical slide image, and determines a dataset type of the medical slide image and a panel of the medical slide image. The computing device assigns to an annotator account, an annotation job defined by at least the medical slide image, the determined dataset type, an annotation task, and a patch that is a partial area of the medical slide image. The annotation task includes the determined panel, and the panel is designated as one of a plurality of panels including a cell panel, a tissue panel, and a structure panel. The dataset type indicates a use of the medical slide image and is designated as one of a plurality of uses including a training use of a medical learning model and a validation use of the machine learning model.
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 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
G06V 10/778 - Active pattern-learning, e.g. online learning of image or video features
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilitiesICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
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
58.
METHOD AND APPARATUS FOR ANALYZING PATHOLOGICAL SLIDE IMAGE
A computing apparatus according to an aspect comprises at least one memory and at least one processor, wherein the processor: acquires a first pathological slide image in which at least one first object has been expressed and biological information of the at least one first object; generates training data by using at least one first patch included in the first pathological slide image and the biological information; trains a first machine learning model by means of the training data; and analyzes a second pathological slide image by using the trained first machine learning model.
G01N 21/78 - Systems in which material is subjected to a chemical reaction, the progress or the result of the reaction being investigated by observing the effect on a chemical indicator producing a change of colour
G01N 33/531 - Production of immunochemical test materials
G01N 33/574 - ImmunoassayBiospecific binding assayMaterials therefor for cancer
59.
Method and device for analyzing pathological slide image
Provided is a computing device including at least one memory, and at least one processor configured to obtain a first pathological slide image one of a first object and biological information of the first object, generate training data by using at least one first patch included in the first pathological slide image, and the biological information, train a first machine learning model based on the training data, and analyze a second pathological slide image of a second object by using the trained first machine learning model.
A method for interpreting an input image by a computing device operated by at least one processor is provided. The method for interpreting an input image comprises storing an artificial intelligent (AI) model that is trained to classify a lesion detected in the input image as suspicious or non-suspicious and, under a condition of being suspicious, to classify the lesion detected in the input image as malignant or benign-hard representing that the lesion is suspicious but determined to be benign, receiving an analysis target image, by using the AI model, obtaining a classification class of a target lesion detected in the analysis target image and, when the classification class is the suspicious, obtaining at least one of a probability of being suspicious, a probability of being benign-hard, and a probability of malignant for the target lesion, and outputting an interpretation result including at least one probability obtained for the target lesion.
G06V 10/40 - Extraction of image or video features
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
61.
Method and apparatus for selecting medical data for annotation
An operating method of a medical data selecting apparatus operated by at least one processor includes generating training data including partial medical data sampled from mass medical data and annotated data of the partial medical data, extracting candidate data for annotation from the mass medical data, the candidate data being at least a portion of the mass medical data, acquiring inference results that are inferred from the candidate data by an artificial intelligence (AI) model trained based on the training data and selecting target data for annotation to be used in next training of the AI model, from among the candidate data based on the inference results.
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
62.
Method and system for analyzing pathological image
The present disclosure relates to a method, performed by at least one processor of an information processing system, of analyzing a pathological image. The method includes receiving a pathological image, detecting an object associated with medical information, in the received pathological image by using a machine learning model, generating an analysis result on the received pathological image, based on a result of the detecting, and outputting medical information about at least one region included in the pathological image, based on the analysis result.
Provided are a method and an apparatus for interlocking a lesion location between a 2D medical image and 3D tomosynthesis images including a plurality of 3D image slices.
G06T 3/40 - Scaling of whole images or parts thereof, e.g. expanding or contracting
G06T 15/00 - 3D [Three Dimensional] image rendering
64.
APPARATUS AND METHOD FOR LINKING LESION LOCATION BETWEEN GUIDE IMAGE AND 3D TOMOSYNTHESIS IMAGES INCLUDING PLURALITY OF 3D IMAGE SLICES, AND PROVIDING LINKED IMAGE
The present disclosure relates to a method and apparatus for linking a lesion location between a 2D medical image and 3D tomosynthesis images which include a plurality of 3D image slices, and providing the linked image.
Provided is a computing apparatus including: at least one memory; and at least one processor, wherein the at least one processor is configured to: perform a first classification on a plurality of tissues expressed in a pathological slide image by analyzing the pathological slide image, perform a second classification on a plurality of cells expressed in a pathological slide image by analyzing the pathological slide image, and calculate tumor purity including information on noise included in the pathological slide image by combining a first classification result and a second classification result.
G16B 20/00 - ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
G16B 40/00 - ICT specially adapted for biostatisticsICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
Provided is a computing apparatus including: at least one memory; and at least one processor, wherein the at least one processor is configured to: perform a first classification on a plurality of tissues expressed in a pathological slide image by analyzing the pathological slide image, perform a second classification on a plurality of cells expressed in a pathological slide image by analyzing the pathological slide image, and calculate tumor purity including information on noise included in the pathological slide image by combining a first classification result and a second classification result.
A method of outputting a pathology slide image includes receiving a user input related to a method of outputting at least one region included in the pathology slide image, based on the user input, determining an area of a guide to be output on the pathology slide image and a region of the pathology slide image included in the guide, and based on the determined area and region, outputting the pathology slide image on which the guide is overlaid.
A method of outputting a pathology slide image includes receiving a user input related to a method of outputting at least one region included in the pathology slide image, based on the user input, determining an area of a guide to be output on the pathology slide image and a region of the pathology slide image included in the guide, and based on the determined area and region, outputting the pathology slide image on which the guide is overlaid.
G06F 3/147 - Digital output to display device using display panels
G16H 80/00 - ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
G06F 3/04845 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range for image manipulation, e.g. dragging, rotation, expansion or change of colour
G06F 3/0482 - Interaction with lists of selectable items, e.g. menus
69.
Method and system for determining abnormality in medical device
A method for determining an abnormality in a medical device from a medical image is provided. The method for determining an abnormality in a medical device comprises receiving a medical image, and detecting information on at least a part of a target medical device included in the received medical image.
Provided is a computing apparatus including: at least one memory; and at least one processor, wherein the at least one processor is configured to: perform a first classification on a plurality of tissues expressed in a pathological slide image by analyzing the pathological slide image, perform a second classification on a plurality of cells expressed in a pathological slide image by analyzing the pathological slide image, and calculate tumor purity including information on noise included in the pathological slide image by combining a first classification result and a second classification result.
A computing apparatus includes: at least one memory; and at least one processor, wherein the processor generates quantitative information regarding at least one cell included in a region of interest of a pathological slide image by analyzing the pathological slide image, generates qualitative information regarding at least one tissue included in the pathological slide image by analyzing the pathological slide image, and controls a display apparatus to output at least one of the quantitative information and the qualitative information on the pathological slide image according to a manipulation of a user.
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
72.
Method for filtering normal medical image, method for interpreting medical image, and computing device implementing the methods
A method of reading a medical image by a computing device operated by at least one processor is provided. The method includes obtaining an abnormality score of the input image using an abnormality prediction model, filtering the input image so as not to be subsequently analyzed when the abnormality score is less than or equal to a cut-off score based on the cut-off score which makes a specific reading sensitivity; and obtaining an analysis result of the input image using a classification model that distinguishes the input image into classification classes when the abnormality score is greater than the cut-off score.
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
SEOUL NATIONAL UNIVERSITY HOSPITAL (Republic of Korea)
Inventor
Kim, Min Chul
Park, Chang Min
Hwang, Eui Jin
Abstract
Some embodiments of the present disclosure provide a pneumothorax detection method performed by a computing device. The method may comprise obtaining predicted pneumothorax information, predicted tube information, and a predicted spinal baseline with respect to an input image from a trained pneumothorax prediction model; determining at least one pneumothorax representative position for the predicted pneumothorax information and at least one tube representative position for the predicted tube information, in a prediction image in which the predicted pneumothorax information and the predicted tube information are displayed; dividing the prediction image into a first region and a second region by the predicted spinal baseline; and determining a region in which the at least one pneumothorax representative position and the at least one tube representative position exist among the first region and the second region.
G06T 7/70 - Determining position or orientation of objects or cameras
G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
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
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
74.
METHOD AND APPARATUS FOR PROVIDING EXAMINATION-RELATED GUIDE ON BASIS OF TUMOR CONTENT PREDICTED FROM PATHOLOGY SLIDE IMAGES
A computing device according to an aspect includes at least one memory and at least one processor. The processor analyzes pathology slide images to obtain information related to tissues or cells represented in the pathology slide images, predicts the ratio of circulating tumor DNA to cell free DNA on the basis of the information, and creates a guide related to subsequent examinations on the basis of the ratio.
G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
G16B 45/00 - ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks
G16B 20/20 - Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
G16B 30/00 - ICT specially adapted for sequence analysis involving nucleotides or amino acids
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
75.
METHOD AND DEVICE FOR OUTPUTTING INFORMATION RELATED TO PATHOLOGICAL SLIDE IMAGE
A computing device according to one aspect comprises at least one memory and at least one processor, wherein the processor analyzes the pathological slide image so as to generate quantitative information about at least one cell included in a region of interest of the pathological slide image, analyzes the pathological slide image so as to generate qualitative information about at least one tissue included in the pathological slide image, and controls a display device so as to output the quantitative information and/or the qualitative information on the pathological slide image according to operation by a user.
G06T 3/40 - Scaling of whole images or parts thereof, e.g. expanding or contracting
G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
G06F 3/0484 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
G06T 7/187 - SegmentationEdge detection involving region growingSegmentationEdge detection involving region mergingSegmentationEdge detection involving connected component labelling
A method for parallel processing a digitally scanned pathology image is performed by a plurality of processors and includes performing, by a first processor, a first operation of generating a first batch from a first set of patches extracted from a digitally scanned pathology image and providing the generated first batch to a second processor, performing, by the first processor, a second operation of generating a second batch from a second set of patches extracted from the digitally scanned pathology image and providing the generated second batch to the second processor, and performing, by the second processor, a third operation of outputting a first analysis result from the first batch by using a machine learning model, with at least part of time frame for the second operation performed by the first processor overlapping at least part of time frame for the third operation performed by the second processor.
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 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
77.
Method and system for determining abnormality in medical device
A method for determining an abnormality in a medical device from a medical image is provided. The method for determining an abnormality in a medical device comprises receiving a medical image, and detecting information on at least a part of a target medical device included in the received medical image.
The present invention relates to a method for generating an interpretable prediction result for a patient, wherein the method is performed by at least one computing device. The method comprises the steps of: receiving medical image data of a patient in question; receiving additional medical data of the patient in question; and using a machine learning prediction model to generate information about a prediction result for the patient in question on the basis of the medical image data of the patient in question and the additional medical data of the patient in question.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
Provided is a method, performed by at least one computing apparatus, of generating an interpretable prediction result for a patient. The method includes receiving medical image data of a subject patient, receiving additional medical data of the subject patient, and generating information about a prediction result for the subject patient, based on the medical image data of the subject patient and the additional medical data of the subject patient, by using a machine learning prediction model.
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
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
80.
AI INSURANCE SERVER AND METHOD FOR PROVIDING AI INSURANCE SERVICE
Provided are an artificial intelligence insurance server and a method for providing an artificial intelligence insurance service. The artificial intelligence insurance server comprises a receiving unit for receiving input data including medical data of an insurance user, a comparison data selection unit for selecting comparison data based on the input data, and deriving first analysis data by analyzing the comparison data, an artificial intelligence analysis unit for obtaining second analysis data derived by performing artificial intelligence analysis on the input data, a comparison unit for comparing the first and the second analysis data and generating final analysis data using the first and the second analysis data and a decision-making unit for making at least one insurance-related decision using the final analysis data.
The present disclosure provides a pathology image analysis method performed by at least one processor. This method comprises the steps of: acquiring pathology images; inputting the acquired pathology images to a machine-learning model and acquiring an analysis result for the pathology images from the machine-learning model; and outputting the acquired analysis result, wherein the machine-learning model may be a model trained by using a training data set generated on the basis of a first pathology data set associated with a first domain and a second pathology data set associated with a second domain different from the first domain.
09 - Scientific and electric apparatus and instruments
10 - Medical apparatus and instruments
38 - Telecommunications services
42 - Scientific, technological and industrial services, research and design
Goods & Services
X-ray spectroscopes; software as a medical device [SaMD],
downloadable; computer software for data processing;
computer software for database; database management
software; data communication apparatus and instruments;
computer software for processing digital images; monitors
[computer programs]; magnetic resonance imaging [MRI]
apparatus, not for medical purposes; bioinformatics
software; image analyzers; apparatus for recording,
transmission and reproduction of images; computer software
for image processing; computer software for making
electronic charts, for medical purposes; computer software
for diagnosing diseases for medical purposes; computer
software for use in medical decision support systems;
computer application software for mobile phones; electronic
imaging devices. Electromedical apparatus and equipment for X-ray diagnostics
and X-ray therapy; X-ray diagnostic apparatus; medical
measuring instruments for cancer diagnosis; medical
apparatus and instruments for displaying diagnostic tests;
medical CT scanners; peripheral devices of medical CT
scanners; X-ray structure analysis instruments for medical
use; diagnostic testing instruments for use in immunoassay
procedure [medical]; immunofluorescence analysis apparatus
for medical purposes; apparatus for analysing images [for
medical use]; medical imaging apparatus; medical diagnostic
imaging apparatus; magnetic resonance imaging [MRI]
apparatus for medical purposes; diagnostic imaging apparatus
for medical use; diagnostic, examination, and monitoring
apparatus and instruments for medical purposes; scanners for
medical diagnosis; automatic analyzers for medical
diagnosis; diagnostic apparatus for medical purposes; MRI
diagnostic apparatus; ultrasound displaying diagnostic
apparatus. Transmission and reception of information and data via
telecommunication networks; transmission of data/sound or
images; providing access to databases or internet
information; transmission of digital image; transmission of
digital files; electronic transmission of sound, images and
other data and information of all kinds; transmission of
text message and video; transmission of text, photo and
video via the smart phone application; electronic
transmission and delivery of audio and visual content;
providing on-line access to databases; transmission and
reception (transmission) of database information via the
wired or wireless telecommunication network; network
transmission of sounds, images, signals and data;
transmission of sound/text data/images; electronic
transmission of sound, images and other data and information
of all kinds via the internet; provision of access to
medical information via the internet; telegram transmission;
information transfer; communications by computer terminals;
computer aided transmission of information and images; video
conferencing communications. Data warehousing; development of data bases; research
relating to data processing; scientific research for medical
purposes in the area of cancerous diseases; computer
programming in the medical field; remote monitoring services
for medical diagnostic devices (remote monitoring of medical
diagnostic systems); research and development of medical
apparatus and instruments for others; scientific research
for medical purposes; operating software development for
others in the field of medical digital X-ray medical
equipment; programming of software for providing management
assistance services in relation to medical image data;
design of medical diagnostic apparatus and instruments;
research and development of medical equipment; development
of computer software for use with medical equipment;
providing computer software technical support services in
the field of medical diagnostics; technological and
scientific monitoring services relating to medical
diagnostic instruments; computer programming services for
remote management of medical diagnostic systems; medical
research laboratory services for predicting disease; medical
research; development and testing of computer software;
computer software development.
83.
Medical imaging device and medical image processing method
A method for operating a medical imaging device includes obtaining lesion information on at least one lesion detected from a medical image, determining a shape and a position of at least one contour corresponding to the at least one lesion based on the obtained lesion information, determining a position of at least one text region that includes a text indicating the lesion information on the at least one lesion in the medical image, and displaying the at least one contour and the text included in the at least one text region on the medical image, based on the determined shape and position of the at least one contour and the determined position of the at least one text region.
G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]Salient regional features
G06T 7/70 - Determining position or orientation of objects or cameras
G06T 11/20 - Drawing from basic elements, e.g. lines or circles
G06V 10/25 - Determination of region of interest [ROI] or a volume of interest [VOI]
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersectionsConnectivity analysis, e.g. of connected components
G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
09 - Scientific and electric apparatus and instruments
10 - Medical apparatus and instruments
38 - Telecommunications services
42 - Scientific, technological and industrial services, research and design
44 - Medical, veterinary, hygienic and cosmetic services; agriculture, horticulture and forestry services
Goods & Services
X-ray spectroscopes; software as a medical device [SaMD],
downloadable; computer software for data processing;
computer software for database; database management
software; data communication apparatus and instruments;
computer software for processing digital images; monitors
[computer programs]; magnetic resonance imaging [MRI]
apparatus, not for medical purposes; bioinformatics
software; image analyzers; apparatus for recording,
transmission and reproduction of images; computer software
for image processing; computer software for making
electronic charts, for medical purposes; computer software
for diagnosing diseases for medical purposes; computer
software for use in medical decision support systems;
computer application software for mobile phones; electronic
imaging devices. Electromedical apparatus and equipment for X-ray diagnostics
and X-ray therapy; X-ray diagnostic apparatus; medical
measuring instruments for cancer diagnosis; medical
apparatus and instruments for displaying diagnostic tests;
medical CT scanners; peripheral devices of medical CT
scanners; X-ray structure analysis instruments for medical
use; diagnostic testing instruments for use in immunoassay
procedure [medical]; immunofluorescence analysis apparatus
for medical purposes; apparatus for analysing images [for
medical use]; medical imaging apparatus; medical diagnostic
imaging apparatus; magnetic resonance imaging [MRI]
apparatus for medical purposes; diagnostic imaging apparatus
for medical use; diagnostic, examination, and monitoring
medical apparatus and instruments; scanners for medical
diagnosis; automatic analyzers for medical diagnosis;
diagnostic apparatus for medical purposes; MRI diagnostic
apparatus; ultrasound displaying diagnostic apparatus. Transmission and reception of information and data via
telecommunication networks; transmission of data/sound or
images; providing access to databases or internet
information; transmission of digital image; transmission of
digital files; electronic transmission of sound, images and
other data and information of all kinds; transmission of
text message and video; transmission of text, photo and
video via the smart phone application; electronic
transmission and delivery of audio and visual content;
providing on-line access to databases; transmission and
reception (transmission) of database information via the
wired or wireless telecommunication network; network
transmission of sounds, images, signals and data;
transmission of sound/text data/images; electronic
transmission of sound, images and other data and information
of all kinds via the Internet; provision of access to
medical information via the internet; telegram transmission;
information transfer; communications by computer terminals;
computer aided transmission of information and images; video
conferencing communications. Data warehousing; development of data bases; research
relating to data processing; scientific research for medical
purposes in the area of cancerous diseases; computer
programming in the medical field; remote monitoring services
for medical diagnostic devices (remote monitoring of medical
diagnostic systems); research and development of medical
apparatus and instruments for others; scientific research
for medical purposes; operating software development for
others in the field of medical digital X-ray medical
equipment; technological analysis assistance services for
medical image data; design of medical diagnostic apparatus
and instruments; research and development of medical
equipment; development of computer software for use with
medical equipment; providing computer software technical
support services in the field of medical diagnostics;
technological and scientific monitoring services relating to
medical diagnostic instruments; computer programming
services for remote management of medical diagnostic
systems; medical research laboratory services for predicting
disease; medical research; development and testing of
computer software; computer software development. Medical examination of individuals (provision of reports
relating to the -); managed health care services; physical
examination services; medical analysis for the diagnosis and
treatment of persons; providing information in the field of
cancer prevention, screening, diagnosis and treatment; RNA
or DNA analysis for cancer diagnosis and prognosis; medical
analysis services for cancer diagnosis and prognosis;
medical analysis services for the diagnosis of cancer;
medical analysis services; health care services for treating
cancer; providing cancer screening services; telemedicine
services; providing health information via a web site;
breast cancer screening services; medical information;
medical diagnostic services; medical testing services
relating to the diagnosis and treatment of disease; medical
services for the diagnosis of conditions of the human body;
cervical cancer screening services; bowel cancer screening
services.
85.
METHOD AND SYSTEM FOR MEASURING SIZE CHANGE OF TARGET LESION IN X-RAY IMAGE
The present disclosure pertains to a method for measuring a size change of a target lesion in X-ray images. The method may comprise the steps of: receiving a first X-ray image including the target lesion and a second X-ray image including the target lesion; calculating an occupancy ratio of an area corresponding to the target lesion relative to a reference area in each of the first X-ray image and the second X-ray image; and measuring a size change of the target lesion on the basis of the calculated occupancy ratio.
The present invention relates to a computing apparatus operated by at least one processor, the computing apparatus comprising: a target artificial intelligence model for outputting a target result by learning at least one task and performing a task for an input medical image; and a confidence prediction model for acquiring at least one impact factor affecting the target result, on the basis of the input medical image, and inferring confidence information of the target result by using the impact factor.
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
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G06N 3/04 - Architecture, e.g. interconnection topology
A prediction device operated by means of at least one processor comprises: a risk factor inference model which is an artificial intelligence model trained to infer risk factors of a disease from an input image, and which receives a medical image and outputs at least one inferred risk factor; and a medical prediction model for receiving patient information that includes the at least one inferred risk factor, and outputting a medical prediction including disease risk.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
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
G16H 70/60 - ICT specially adapted for the handling or processing of medical references relating to pathologies
This disclosure relates to a computerized method to perform a machine learning on a relationship between medical images and metadata using a neural network and acquiring metadata by applying a machine learning model to medical images, and a method thereof. The apparatus and method may include training a prediction model for predicting metadata of medical images based on multiple medical images for learning and metadata matched with each of multiple medical images and predicting metadata of input medical image.
A method for detecting a region of interest (ROI) in a pathological slide image is provided. The method may include receiving one or more pathological slide images and detecting an ROI in the received one or more pathological slide images. In addition, an information processing system is provided. The information processing system includes a memory storing one or more instructions, and a processor configured to execute the stored one or more instructions to receive one or more pathological slide images and detect an ROI in the received one or more pathological slide images.
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
G16H 70/60 - ICT specially adapted for the handling or processing of medical references relating to pathologies
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
90.
METHOD AND SYSTEM FOR PREDICTING RISK OF OCCURRENCE OF LESION
The present disclosure relates to a method, for predicting a risk of an occurrence of a lesion, performed by at least one processor. The method may comprise the steps of: obtaining a captured medical image of a subject; predicting the possibility of an occurrence of a legion in the subject from the obtained medical image, by means of a machine learning model; and outputting the prediction result. The machine learning model may be a model which has learned a plurality of training medical images and the risk of an occurrence of a lesion associated with each training medical image.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
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
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
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
A method, performed by at least one processor, for training a machine learning model for detecting an abnormal region in a pathological slide image is disclosed. The method including receiving one or more first pathological slide images, determining, from the received one or more first pathological slide images, a normal region based on an abnormality condition indicative of a condition of an abnormal region, generating a first set of training data including the determined normal region, generating the abnormal region by performing image processing corresponding to the abnormality condition with respect to at least partial region in the received one or more first pathological slide images, and generating a second set of training data including the generated abnormal region.
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
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
92.
METHOD AND SYSTEM FOR ANALYZING PATHOLOGICAL IMAGE
The present disclosure relates to a method for analyzing pathological images, carried out by at least one processor of an information processing system. The method comprises the steps of: receiving a pathological image; detecting a subject associated with medical information from the received pathological image by using a machine learning model; generating an analysis result for the received pathological image on the basis of the detection result; and outputting medical information for at least a partial area included in the pathological image on the basis of the analysis result.
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
A method for interpreting an input image by a computing device operated by at least one processor is provided. The method for interpreting an input image comprises storing an artificial intelligent (AI) model that is trained to classify a lesion detected in the input image as suspicious or non-suspicious and, under a condition of being suspicious, to classify the lesion detected in the input image as malignant or benign-hard representing that the lesion is suspicious but determined to be benign, receiving an analysis target image, by using the AI model, obtaining a classification class of a target lesion detected in the analysis target image and, when the classification class is the suspicious, obtaining at least one of a probability of being suspicious, a probability of being benign-hard, and a probability of malignant for the target lesion, and outputting an interpretation result including at least one probability obtained for the target lesion.
G06V 10/40 - Extraction of image or video features
G06V 10/764 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
09 - Scientific and electric apparatus and instruments
10 - Medical apparatus and instruments
42 - Scientific, technological and industrial services, research and design
44 - Medical, veterinary, hygienic and cosmetic services; agriculture, horticulture and forestry services
Goods & Services
Transmission and reception of information and data via telecommunication networks; electronic transmission of data, sound or images; providing access to databases; electronic transmission of digital images; transmission of digital files; electronic transmission of sound, images and other data and information of all kinds via the Internet; electronic transmission of text message and video; electronic transmission of data, namely, transmission of text, photo and video via the smart phone application; electronic transmission of audio and visual content; providing on-line access to databases; transmission and reception of database information via wired and wireless telecommunication networks; network transmission of sounds, images, signals and data; providing access to an electronic exchange of medical records across a nationwide health information network; transmission of telegrams; information transfer, namely, electronic transmission of data via a computer network; communications by computer terminals; computer aided transmission of information and images; video conferencing services X-ray spectroscopes; software as a medical device (SaMD), namely, downloadable computer software for diagnosing and analyzing disease; downloadable computer software for data processing in the field of medical diagnostic information; downloadable computer software for database management for diagnosing and analyzing disease; downloadable database management software in the field of medical diagnostic information; electronic apparatus for the communication of data, namely, for recording and transmitting audio, video, still images and electronic data; downloadable computer software for processing digital images; recorded computer programs for monitoring of cancer presence or indicators in patients; magnetic resonance imaging (MRI) apparatus, not for medical purposes; downloadable and recorded bioinformatics software for collecting, analyzing, sharing, and monitoring biological data in patients; image analyzers, namely, scanners for capturing images for analysis for use in the medical research and pharmaceutical research field; apparatus for recording, transmission and reproduction of images; downloadable computer software for image processing; downloadable computer software for making electronic charts, for medical purposes; downloadable computer software for diagnosing diseases for medical purposes; downloadable computer software for use in medical decision support systems, namely, software that provides information about options for medical treatment; downloadable computer application software for mobile phones, namely, software that provides information about options for medical treatment; image processing apparatus, namely, computers, image intensifiers, computer display monitors, video cameras Electromedical apparatus and equipment for X-ray diagnostics and X-ray therapy, namely, X-ray diagnostic apparatus, X-ray apparatus for medical use; X-ray diagnostic apparatus; medical measuring instruments for measuring breast tissue density and lung nodule size for cancer diagnosis; medical apparatus and instrument for diagnostic use, namely, apparatus for medical diagnostic testing in the fields of cancer or other tissue-based diagnostic testing, cytology and cell-based testing; medical CT scanners, namely, computed tomography apparatus; peripheral devices of medical CT scanners, namely, integral components of the image chain of a CT scanner for capturing X-rays and converting them to information that creates the image; X-ray apparatus for medical use, namely, X-ray structure analysis instruments for medical use; medical diagnostic testing instruments for use in immunoassay procedure; immunofluorescence analysis apparatus for medical purposes being immunoassay analyzers for medical diagnostic uses; apparatus for analysing images for medical use for diagnosing and analyzing diseases being cancer; medical image processors; medical diagnostic imaging apparatus; magnetic resonance imaging (MRI) apparatus for medical purposes; diagnostic imaging apparatus for medical use; diagnostic, examination and monitoring apparatus for medical purposes, namely, the detection, diagnosis and treatment of cancer; scanners for medical diagnosis, namely, magnetic resonance imaging (MRI) diagnostic apparatus for medical purposes; automatic analyzers for medical diagnosis of diseases, disorders and conditions in the fields of cancer or other tissue-based diagnostic testing, cytology and cell-based testing; medical diagnostic apparatus for medical purposes, namely, diagnostic apparatus for detection of cancer; MRI diagnostic apparatus, for medical purpose; medical ultrasound imaging diagnostic apparatus Data warehousing; database development services; research relating to data processing; scientific research for medical purposes in the area of cancerous diseases; computer programming in the medical field; product research and development of medical apparatus and instruments for others; scientific research for medical purposes in the field of cancerous diseases; operating software development for others in the field of medical digital X-ray medical equipment; technological analysis assistance services for medical image data, namely, analyzing technology requirements and developing recommendations for the computer software and systems and other technology needed to meet those requirements, in the field of medicine; design of medical diagnostic apparatus and instruments; research and development of medical equipment; development of computer software for use with medical equipment; providing computer software technical support services in the field of medical diagnostics, namely, troubleshooting of computer software problems; technological and scientific monitoring services relating to medical diagnostic instruments, namely, monitoring technological functions of computer network systems; computer programming services for remote management of medical diagnostic systems; scientific research and analysis in the field of predicting disease; medical research in the field of medical image data; development and testing of computer software; development and testing of computer software for medical applications Medical reporting services, namely, providing medical information to medical professionals and patients in the form of reports relating to the medical examination of individuals; managed health care services; physical examination services; medical analysis for the diagnosis and treatment of persons; providing information in the field of cancer prevention, screening, diagnosis and treatment; genetic testing for medical purposes, namely, RNA or DNA analysis for cancer diagnosis and prognosis; medical analysis services for cancer diagnosis and prognosis; medical analysis services for the diagnosis of cancer; health care services for treating cancer; providing cancer screening services; telemedicine services; providing health information via a web site; providing breast cancer screening services; provision of medical information; medical diagnostic testing, monitoring and reporting services; medical services for the diagnosis of conditions of the human body, namely, cancer; cervical cancer screening services; bowel cancer screening services; remote monitoring services for medical diagnostic devices and systems, namely, remote monitoring of medical data for medical diagnosis and treatment
09 - Scientific and electric apparatus and instruments
10 - Medical apparatus and instruments
38 - Telecommunications services
42 - Scientific, technological and industrial services, research and design
Goods & Services
(1) X-ray spectroscopes; software as a medical device (SaMD), namely, downloadable computer software for diagnosing and treatment of cancer; downloadable software as a medical device [SaMD] for wireless remote control of and synchronization of computed tomography [CT] apparatus; downloadable software as a medical device [SaMD] for wireless remote control of and synchronization of x-ray machines; downloadable computer software for data processing in the field of medical diagnostic information; downloadable computer software for database management; database management software, downloadable; audio transmitter units; audio recorders; digital video recorders; digital voice recorders; video transmitters; image scanners; downloadable computer software for processing digital images; recorded computer programs for use in the diagnosis, monitoring and treatment of cancer; computer application software for processing and analysis of magnetic resonance imaging (MRI); bioinformatics software; image analyzers for analysis for use in the medical research and pharmaceutical research field; apparatus for recording, transmission and reproduction of images, namely computers, image intensifier tubes, video cameras; downloadable computer software for image processing; downloadable computer software for making electronic charts, for medical purposes; downloadable computer software for diagnosing diseases for medical purposes; downloadable computer software for use in medical decision support systems; downloadable computer application software for mobile phones, namely, software that provides information about diagnostic results and options for medical treatment.
(2) Electromedical apparatus and equipment for X-ray diagnostics and X-ray therapy; X-ray diagnostic apparatus; medical measuring instruments for cancer diagnosis; medical apparatus and instruments, namely, digital radiography machines, ultrasound machines, in-vitro diagnostic machines, medical imaging transducers and computed tomography (CT) apparatus; medical CT scanners; peripheral devices of medical CT scanners; X-ray structure analysis instruments for medical use; diagnostic testing instruments for use in immunoassay procedure [medical]; immunofluorescence analysis apparatus for medical purposes; ultrasonic imaging apparatus for medical purposes; medical image processors; medical diagnostic imaging apparatus; magnetic resonance imaging [MRI] apparatus for medical purposes; diagnostic imaging apparatus for medical use; breast cancer diagnostic devices for measuring breast density and breast lesion size; medical diagnostic apparatus for measuring breast density and breast lesion size; medical diagnostic apparatus for detecting breast cancer; lung cancer diagnostic devices for measuring lung nodule size; medical diagnostic apparatus for measuring lung nodule size; medical diagnostic apparatus for detecting lung cancer; diagnostic biomolecule and DNA sequence detection devices for clinical medical purposes; diagnostic biomolecule and DNA sequence readers of biomolecule and DNA sequence testing results for clinical medical use; medical instruments for taking human blood, cell, saliva, urine and sputum sample specimens for medical purposes; cytology brushes; body fluids analyzer for medical purpose; atomizers sold empty for medical purposes; diagnostic biomarker testing apparatus for use in diagnosis of cancer; diagnostic biomarker expression, gene mutation, and RNA level detection devices for clinical medical purposes; medical diagnostic apparatus for detecting biomarkers in blood; gene testing medical apparatus for identification of genus specific and species specific DNA and RNA sequences; medical apparatus and instruments for amplifying nucleic acid DNA and RNA molecules; cat scanners; x-ray CT scanners; automatic analyzers for diagnosing cancer; medical diagnostic apparatus for medical purposes, namely, diagnostic apparatus for detection of cancer; MRI diagnostic apparatus; ultrasound displaying diagnostic apparatus. (1) Telecommunication services, namely, transmission of voice, images, graphics, audio, video, and multimedia by means of wired and wireless networks; e-mail transmission services; peer-to-peer (p2p) sharing services, namely electronic transmission of digital videos, images, and text over electronic communications networks; transmission of medical data via the internet; transmission of images via cellular telephones; providing access to databases; computer aided transmission of images, namely, transmission of diagnostic ultrasound images via a global computer network; electronic transmission of text messages and video; electronic transmission and delivery of digital music, voice message, photographs, and video data of diagnostic ultrasound images via wireless communication networks and the internet; information transmission via electronic communications networks, namely, transmission of medical administration information via a global computer network; transmission of images over the internet; transmission of text via cellular telephones; provision of access to medical information via the internet; telegram transmission; information transfer, namely, electronic transmission of data in the nature of medical diagnostic information via a computer network; communication by computer terminals, namely, email services, electronic transmission of data, messages, and documents via computer terminals in the nature of medical diagnostic information and medical images; computer aided transmission of information and images in the nature of compiling, analyzing, and transferring medical industry data and medical administration data for healthcare businesses; video conferencing communications.
(2) Data warehousing; development of data bases; research relating to data processing; scientific research for medical purposes in the area of cancerous diseases; computer programming in the medical field; remote monitoring services for medical diagnostic devices (remote monitoring of medical diagnostic systems); research and development of medical apparatus and instruments for others; scientific research for medical purposes; operating software development for others in the field of medical digital X-ray medical equipment; technological analysis assistance services for medical image data; design of medical diagnostic apparatus and instruments; research and development of medical equipment; development of computer software for use with medical equipment; providing computer software technical support services in the field of medical diagnostics; technological and scientific monitoring services relating to medical diagnostic instruments; computer programming services for remote management of medical diagnostic systems; medical research laboratory services for predicting disease; medical research; development and testing of computer software; computer software development.
96.
TRAINING METHOD FOR SPECIALIZING ARTIFICIAL INTERLLIGENCE MODEL IN INSTITUTION FOR DEPLOYMENT, AND APPARATUS FOR TRAINING ARTIFICIAL INTELLIGENCE MODEL
A training method for specializing an artificial intelligence model in an institution for deployment and an apparatus for performing training the artificial intelligence model are provided. A method for operating a training apparatus operated by at least one processor includes extracting a dataset to be used for specialized training from data retained by a certain institution, selecting an annotation target for which annotation is required from the dataset by using a pre-trained artificial intelligence (AI) model, and performing supervised training of the pre-trained AI model by using data annotated with a label for the annotation target.
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
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
97.
Method and system for performing prediction work on target image
Provided is a method for performing a prediction work on a target image, including dividing the target image into a plurality of sub-images, generating prediction results for a plurality of pixels included in each of the plurality of divided sub-images, applying weights to the prediction results for the plurality of pixels, and merging the prediction results for the plurality of pixels applied with the weights.
G06F 18/2415 - Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate
A method for predicting responsiveness to therapy for cancer patient is provided, which includes acquiring a pathology slide image of a cancer patient, determining information on a plurality of lymphocytes and information on a plurality of tumor cells included in the pathology slide image, calculating a lymphocyte and tumor cell interaction score based on the information on the plurality of lymphocytes and the information on the plurality of tumor cells, and predicting responsiveness to therapy for the cancer patient by using the interaction score.
C12Q 1/6886 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
The present disclosure relates to a method for performing a prediction operation on a target image. The method may comprise the steps of: dividing a target image into a plurality of sub-images; generating prediction results for a plurality of pixels included in each of the plurality of divided sub-images; applying a weight to the prediction results for the plurality of pixels; and merging the prediction results for the plurality of pixels to which the weight has been applied.
The present disclosure relates to a medical image analysis method using a processor and a memory which are hardware. The method includes generating predicted second metadata for a medical image by using a prediction model, and determining a processing method of the medical image based on one of first metadata stored corresponding to the medical image and the second metadata.
