An apparatus configured for use with a user interface to manipulate at least one digital while slide image (WSI) displayed on the user interface includes a body, a first control knob, and a second control knob. The first control knob extends from a side of the body and is configured to rotate to control a first manipulation of the digital WSI on the user interface. The second control knob extends from an opposite side of the body and is configured to rotate to control a second manipulation of the digital WSI on the user interface. The first manipulation is different from the second manipulation. At least one of the first control knob or the second control knob is configured to translate to control one or more user interface navigation features associated with the user interface.
G06F 3/04845 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs pour la transformation d’images, p. ex. glissement, rotation, agrandissement ou changement de couleur
G06F 3/0362 - Dispositifs de pointage déplacés ou positionnés par l'utilisateurLeurs accessoires avec détection des translations ou des rotations unidimensionnelles [1D] d’une partie agissante du dispositif de pointage, p. ex. molettes de défilement, curseurs, boutons, rouleaux ou bandes
G06F 3/04847 - Techniques d’interaction pour la commande des valeurs des paramètres, p. ex. interaction avec des règles ou des cadrans
G06F 3/04855 - Interaction avec des barres de défilement
G16H 10/00 - TIC spécialement adaptées au maniement ou au traitement des données médicales ou de soins de santé relatives aux patients
09 - Appareils et instruments scientifiques et électriques
10 - Appareils et instruments médicaux
Produits et services
Automated digital scanning system integrating optical microscopy, motorized sample positioning, digital image capture, data processing, manipulation and display for use in scanning and digitizing microscope samples in research and clinical environments; image analysis devices, namely, scanners; electronic image recording, image storing and image representing devices, namely, digital cameras; computer operating software for image analysis and image storage devices; operating software for automated digital scanning systems; computer software for digitizing microscope slides for viewing, integration with other data, management, and analysis, all in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; digital slide information management software for digitizing glass microscope slides into diagnostic quality images displayed in context with reports, case histories and other associated documents or data, optionally cross-linked and concurrently viewable for use in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; software for tracking the location of histological and cytological specimens; computer software for image data storage and archiving on local servers or networks for use in research and clinical environments Diagnostic apparatus for medical purposes; medical apparatus and instruments, namely, digital slide systems incorporating microscopes, digital cameras, digital slide scanners, equipped with digital image capture and data processing devices for medical/clinical diagnostic purposes
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable and recorded software for receiving,
processing, transmitting, analyzing, and displaying data and
images derived from biological specimens; downloadable and
recorded software for receiving, processing, transmitting,
analyzing, and displaying data and images, in the fields of
virtual microscopy, digital pathology, and digital
hematology; downloadable and recorded software for providing
an interface between scientific and medical apparatus,
instruments, and systems and software for analyzing
biological specimens; downloadable and recorded software for
providing an interface between digital slide and digital
scanning systems and software for image analysis;
downloadable and recorded software for providing an
interface between digital slide information management
software and software for image analysis; downloadable and
recorded software for providing an interface between image
management and viewing systems for medical purposes and
software for analyzing images for medical diagnostic
purposes; downloadable and recorded software for providing
an interface between systems used for medical imaging and
software for analyzing data and images derived from
biological specimens. Software as a service (SaaS) services featuring software for
receiving, processing, transmitting, analyzing, and
displaying data and images derived from biological
specimens; software as a service (SaaS) services featuring
software for receiving, processing, transmitting, analyzing,
and displaying data and images, in the fields of virtual
microscopy, digital pathology, and digital hematology;
software as a service (SaaS) services featuring software for
providing an interface between scientific and medical
apparatus, instruments, and systems and software for
analyzing biological specimens; software as a service (SaaS)
services featuring software for providing an interface
between digital slide and digital scanning systems and
software for image analysis; software as a service (SaaS)
services featuring software for providing an interface
between digital slide information management software and
software for image analysis; software as a service (SaaS)
services featuring software for providing an interface
between image management and viewing systems for medical
purposes and software for analyzing images for medical
diagnostic purposes; software as a service (SaaS) services
featuring software for providing an interface between
systems used for medical imaging and software for analyzing
data and images derived from biological specimens;
installation, repair and maintenance of computer software;
design and development of computer software.
5.
AUTOMATIC TILT COMPENSATION IN A DIGITAL SCANNING SYSTEM
It is possible to digitize a sample using a scanning in a manner which automatically accounts for tilt which may otherwise result in some or all of a digitized image being out of focus. This may be done by obtaining a plurality of segments of image data and combining the plurality of segments of image data into a contiguous digital image of the sample. In this type of scenario, obtaining the plurality of segments of image data may comprise capturing one or more segments using an initial segment width, detecting tilted image data and, based on detecting the tilted image data, determining a narrower segment width and capturing one or more segments using the narrower segment width.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
(1) Downloadable and recorded software for receiving, processing, transmitting, analyzing, and displaying data and images derived from biological specimens; downloadable and recorded software for receiving, processing, transmitting, analyzing, and displaying data and images, in the fields of virtual microscopy, digital pathology, and digital hematology; downloadable and recorded software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; downloadable and recorded software for providing an interface between digital slide and digital scanning systems and software for image analysis; downloadable and recorded software for providing an interface between digital slide information management software and software for image analysis; downloadable and recorded software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; downloadable and recorded software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens. (1) Software as a service (SaaS) services featuring software for receiving, processing, transmitting, analyzing, and displaying data and images derived from biological specimens; software as a service (SaaS) services featuring software for receiving, processing, transmitting, analyzing, and displaying data and images, in the fields of virtual microscopy, digital pathology, and digital hematology; software as a service (SaaS) services featuring software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; software as a service (SaaS) services featuring software for providing an interface between digital slide and digital scanning systems and software for image analysis; software as a service (SaaS) services featuring software for providing an interface between digital slide information management software and software for image analysis; software as a service (SaaS) services featuring software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; software as a service (SaaS) services featuring software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens; installation, repair and maintenance of computer software; design and development of computer software.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable and recorded middleware software; downloadable
and recorded middleware software in the fields of virtual
microscopy, digital pathology, and digital hematology;
downloadable and recorded software for providing an
interface between scientific and medical apparatus,
instruments, and systems and software for analyzing
biological specimens; downloadable and recorded software for
providing an interface between digital slide and digital
scanning systems and software for image analysis;
downloadable and recorded software for providing an
interface between digital slide information management
software and software for image analysis; downloadable and
recorded software for providing an interface between image
management and viewing systems for medical purposes and
software for analyzing images for medical diagnostic
purposes; downloadable and recorded software for providing
an interface between systems used for medical imaging and
software for analyzing data and images derived from
biological specimens. Software as a service (SaaS) services featuring middleware
software; software as a service (SaaS) services featuring
middleware software in the fields of virtual microscopy,
digital pathology, and digital hematology; software as a
service (SaaS) services featuring software for providing an
interface between scientific and medical apparatus,
instruments, and systems and software for analyzing
biological specimens; software as a service (SaaS) services
featuring software for providing an interface between
digital slide and digital scanning systems and software for
image analysis; software as a service (SaaS) services
featuring software for providing an interface between
digital slide information management software and software
for image analysis; software as a service (SaaS) services
featuring software for providing an interface between image
management and viewing systems for medical purposes and
software for analyzing images for medical diagnostic
purposes; software as a service (SaaS) services featuring
software for providing an interface between systems used for
medical imaging and software for analyzing data and images
derived from biological specimens; installation, repair and
maintenance of computer middleware software; design and
development of computer middleware software.
8.
VIEWER WITH AUTOMATIC OPACITY ADJUSTMENT OF IMAGE MASK
An apparatus for interacting with one or more digital whole slide images (WSIs) acquired by an imaging device includes a display, a memory, and one or more hardware processors. The memory' is configured to store computer-executable instructions. The one or more hardware processors are in communication with the display and the memory. The one or more hardware processors are configured to drive the display using the computer-executable instructions of the memory'- such that the one or more hardware processors are configured to generate a. user interface. The user interface includes an image layer and one or more mask layers overlaying the image layer. The one or more mask layers have a predetermined opacity level. The one or more hardware processors are further configured to automatically adjust the predetermined opacity level as a function of a magnification level of the image layer.
G06F 3/04845 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs pour la transformation d’images, p. ex. glissement, rotation, agrandissement ou changement de couleur
G16H 30/40 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le traitement d’images médicales, p. ex. l’édition
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
09 - Appareils et instruments scientifiques et électriques
10 - Appareils et instruments médicaux
Produits et services
Automated digital scanning system integrating optical microscopy, motorized sample positioning, digital image capture, data processing, manipulation and display for use in scanning and digitizing microscope samples in research and clinical environments; image analysis devices, namely, scanners; electronic image recording, image storing and image representing devices, namely, digital cameras; computer operating software for image analysis and image storage devices; operating software for automated digital scanning systems; computer software for digitizing microscope slides for viewing, integration with other data, management, and analysis, all in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; digital slide information management software for digitizing glass microscope slides into diagnostic quality images displayed in context with reports, case histories and other associated documents or data, optionally cross-linked and concurrently viewable for use in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; software for tracking the location of histological and cytological specimens; computer software for image data storage and archiving on local servers or networks for use in research and clinical environments Diagnostic apparatus for medical purposes; medical apparatus and instruments, namely, digital slide systems incorporating microscopes, digital cameras, digital slide scanners, equipped with digital image capture and data processing devices for medical/clinical diagnostic purposes
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
(1) Downloadable and recorded middleware software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens and data and images derived from biological specimens; downloadable and recorded middleware software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens and data and images derived from biological specimens, in the fields of virtual microscopy, digital pathology, and digital hematology; downloadable and recorded software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; downloadable and recorded software for providing an interface between digital slide and digital scanning systems and software for image analysis; downloadable and recorded software for providing an interface between digital slide information management software and software for image analysis; downloadable and recorded software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; downloadable and recorded software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimen. (1) Software as a service (SaaS) services featuring online non-downloadable middleware software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens and data and images derived from biological specimens; software as a service (SaaS) services featuring online non-downloadable middleware software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens and data and images derived from biological specimens, in the fields of virtual microscopy, digital pathology, and digital hematology; software as a service (SaaS) services featuring software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; software as a service (SaaS) services featuring software for providing an interface between digital slide and digital scanning systems and software for image analysis; software as a service (SaaS) services featuring software for providing an interface between digital slide information management software and software for image analysis; software as a service (SaaS) services featuring software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; software as a service (SaaS) services featuring software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens; installation, repair and maintenance of computer middleware software; design and development of computer middleware software.
11.
SYSTEMS AND METHODS FOR CLASSIFICATION OF HISTOPATHOLOGY IMAGES
Systems and methods for classification of histopathology images are disclosed. In one aspect, an apparatus for detecting a medical condition in a histopathology image includes a hardware memory configured to store executable instructions and a hardware processor in communication with the hardware memory, wherein the executable instructions, when executed by the processor, cause the processor to obtain a plurality of patches at a plurality of magnification levels from the histopathology image, apply a deep learning algorithm to each of the patches, extract, from applying the deep learning algorithm, information representative of a hierarchical relationship that links characteristics of the histopathology image present at one level and another level of the plurality of magnification levels, and identify the medical condition based on the extracted information representative of the hierarchical relationship for characteristics present at the one level and at the another level of the plurality of magnification levels.
09 - Appareils et instruments scientifiques et électriques
10 - Appareils et instruments médicaux
Produits et services
Downloadable and recorded computer operating software for automated digital scanning systems; downloadable and recorded computer software for digitizing microscope slides for viewing, integration with other data, management, and analysis, all in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; downloadable and recorded computer software for managing digital microscope slide information, digitizing glass microscope slides into diagnostic quality images displayed in context with reports, case histories and other associated documents or data, and for optionally cross-linking and concurrently viewing microscope slide information and images for use in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; downloadable and recorded software for tracking the location of histological and cytological specimens; downloadable and recorded computer operating software for image analysis and image storage devices; electronic image recording, image storing and image representing devices, namely, digital cameras; Automated digital scanning system integrating optical microscopy, motorized sample positioning, digital image capture, data processing, manipulation and display for use in scanning and digitizing microscope samples in research and clinical laboratory environments, comprised of a microscope, digital camera, microscope slide scanner for digital image capture, and downloadable computer software for digitizing microscope slides, analyzing and storing images, managing and analyzing information relating to scanned microscope samples, and tracking histological and cytological specimen locations , all the foregoing not for medical use apart from medical research; scanners for capturing images for analysis for use in research and clinical laboratory environments, all the foregoing not for medical use apart from medical research; downloadable and recorded computer software for image data storage and archiving on local servers or networks for use in research and clinical environments medical apparatus and instruments, namely, digital slide systems incorporating microscopes, digital cameras, digital slide scanners, equipped with digital image capture and data processing devices for medical and clinical diagnostic purposes in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; medical diagnostic apparatus for the analysis of biological samples
09 - Appareils et instruments scientifiques et électriques
10 - Appareils et instruments médicaux
Produits et services
Downloadable and recorded computer operating software for image analysis and image storage devices; downloadable and recorded computer software for image data storage and archiving on local servers or networks for use in research and clinical environments; electronic image recording, image storing and image representing devices, namely, digital cameras; downloadable and recorded computer software for managing digital microscope slide information, digitizing glass microscope slides into diagnostic quality images displayed in context with reports, case histories and other associated documents or data, and for optionally cross-linking and concurrently viewing microscope slide information and images for use in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; automated digital scanning system integrating optical microscopy, motorized sample positioning, digital image capture, data processing, manipulation and display for use in scanning and digitizing microscope samples in research and clinical laboratory environments, comprised of a microscope, digital camera, microscope slide scanner for digital image capture, and downloadable computer software for digitizing microscope slides, analyzing and storing images, managing and analyzing information relating to scanned microscope samples, and tracking histological and cytological specimen locations, all the foregoing not for medical use apart from medical research; downloadable and recorded computer operating software for automated digital scanning systems; downloadable and recorded computer software for tracking the location of histological and cytological specimens; scanners for capturing images for analysis for use in research and clinical laboratory environments, all the foregoing not for medical use apart from medical research; downloadable and recorded computer software for digitizing microscope slides for viewing, integration with other data, management, and analysis, all in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology Medical diagnostic apparatus for the analysis of biological samples; medical apparatus and instruments, namely, digital slide systems incorporating microscopes, digital cameras, digital slide scanners, equipped with digital image capture and data processing devices for medical and clinical diagnostic purposes in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology
09 - Appareils et instruments scientifiques et électriques
10 - Appareils et instruments médicaux
Produits et services
Downloadable and recorded computer software for managing digital microscope slide information, digitizing glass microscope slides into diagnostic quality images displayed in context with reports, case histories and other associated documents or data, and for optionally cross-linking and concurrently viewing microscope slide information and images for use in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; downloadable and recorded computer software for tracking the location of histological and cytological specimens; Automated digital scanning system integrating optical microscopy, motorized sample positioning, digital image capture, data processing, manipulation and display for use in scanning and digitizing microscope samples in research and clinical laboratory environments, comprised of a microscope, digital camera, microscope slide scanner for digital image capture, and downloadable computer software for digitizing microscope slides, analyzing and storing images, managing and analyzing information relating to scanned microscope samples, and tracking histological and cytological specimen locations, all the foregoing not for medical use apart from medical research; scanners for capturing images for analysis for use in research and clinical laboratory environments, all the foregoing not for medical use apart from medical research; downloadable and recorded computer operating software for automated digital scanning systems; downloadable and recorded computer software for image data storage and archiving on local servers or networks for use in research and clinical environments; downloadable and recorded computer operating software for image analysis and image storage devices; electronic image recording, image storing and image representing devices, namely, digital cameras; downloadable and recorded computer software for digitizing microscope slides for viewing, integration with other data, management, and analysis, all in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology Medical diagnostic apparatus for the analysis of biological samples; medical apparatus and instruments, namely, digital slide systems incorporating microscopes, digital cameras, digital slide scanners, equipped with digital image capture and data processing devices for medical and clinical diagnostic purposes in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology
09 - Appareils et instruments scientifiques et électriques
10 - Appareils et instruments médicaux
Produits et services
Scientific apparatus and instruments, namely, digital slide systems comprised of microscopes, digital cameras, digital slide scanners for digital image capture and data processing for use in research laboratories, all the foregoing not for medical use apart from medical research; downloadable and recorded computer software for data and image measuring and processing for use with microscopes in research laboratories; downloadable and recorded computer software for data and image measuring and processing for use with microscopes in the medical field Medical apparatus and instruments, namely, digital slide systems comprised of microscopes for surgical operations, digital cameras, and digital slide scanners for digital image capture and data processing for medical use
09 - Appareils et instruments scientifiques et électriques
10 - Appareils et instruments médicaux
Produits et services
Scientific apparatus and instruments, namely, digital slide systems comprised of microscopes, digital cameras, digital slide scanners for digital image capture and data processing for use in research laboratories, all the foregoing not for medical use apart from medical research; downloadable and recorded computer software for data and image measuring and processing for use with microscopes in research laboratories; downloadable and recorded computer software for data and image measuring and processing for use with microscopes in the medical field Medical apparatus and instruments, namely, digital slide systems comprised of microscopes for surgical operations, digital cameras, and digital slide scanners for digital image capture and data processing for medical use
09 - Appareils et instruments scientifiques et électriques
10 - Appareils et instruments médicaux
Produits et services
Scientific apparatus and instruments, namely, digital slide systems comprised of microscopes, digital cameras, digital slide scanners for digital image capture and data processing for use in research laboratories, all the foregoing not for medical use apart from medical research; downloadable and recorded computer software for data and image measuring and processing for use with microscopes in research laboratories; downloadable and recorded computer software for data and image measuring and processing for use with microscopes in the medical field Medical apparatus and instruments, namely, digital slide systems comprised of microscopes for surgical operations, digital cameras, and digital slide scanners for digital image capture and data processing for medical use
09 - Appareils et instruments scientifiques et électriques
Produits et services
Automated image analysis computer hardware system comprising
printed circuit boards, hard and floppy disk drives,
keyboard, monitors, printer, plotter, digital scanner, video
camera and camera stand; computer software for cellular
image and chromosome analysis in the field of molecular
biology and genetic research.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable and recorded software for receiving, processing, transmitting, analyzing, and displaying data and images derived from biological specimens; Downloadable and recorded software for receiving, processing, transmitting, analyzing, and displaying data and images, in the fields of virtual microscopy, digital pathology, and digital hematology; Downloadable and recorded software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; Downloadable and recorded software for providing an interface between digital slide and digital scanning systems and software for image analysis; Downloadable and recorded software for providing an interface between digital slide information management software and software for image analysis; Downloadable and recorded software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; Downloadable and recorded software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens Software as a service (SaaS) services featuring software for receiving, processing, transmitting, analyzing, and displaying data and images derived from biological specimens; Software as a service (SaaS) services featuring software for receiving, processing, transmitting, analyzing, and displaying data and images, in the fields of virtual microscopy, digital pathology, and digital hematology; Software as a service (SaaS) services featuring software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; Software as a service (SaaS) services featuring software for providing an interface between digital slide and digital scanning systems and software for image analysis; Software as a service (SaaS) services featuring software for providing an interface between digital slide information management software and software for image analysis; Software as a service (SaaS) services featuring software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; Software as a service (SaaS) services featuring software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens; Installation, repair and maintenance of computer software; Design and development of computer software
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable and recorded middleware software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens and data and images derived from biological specimens; Downloadable and recorded middleware software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens and data and images derived from biological specimens, in the fields of virtual microscopy, digital pathology, and digital hematology; Downloadable and recorded software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; Downloadable and recorded software for providing an interface between digital slide and digital scanning systems and software for image analysis; Downloadable and recorded software for providing an interface between digital slide information management software and software for image analysis; Downloadable and recorded software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; Downloadable and recorded software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens Software as a service (SaaS) services featuring online non-downloadable middleware software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens and data and images derived from biological specimens; Software as a service (SaaS) services featuring online non-downloadable middleware software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens and data and images derived from biological specimens, in the fields of virtual microscopy, digital pathology, and digital hematology; Software as a service (SaaS) services featuring software for providing an interface between scientific and medical apparatus, instruments, and systems and software for analyzing biological specimens; Software as a service (SaaS) services featuring software for providing an interface between digital slide and digital scanning systems and software for image analysis; Software as a service (SaaS) services featuring software for providing an interface between digital slide information management software and software for image analysis; Software as a service (SaaS) services featuring software for providing an interface between image management and viewing systems for medical purposes and software for analyzing images for medical diagnostic purposes; Software as a service (SaaS) services featuring software for providing an interface between systems used for medical imaging and software for analyzing data and images derived from biological specimens; Installation, repair and maintenance of computer middleware software; Design and development of computer middleware software
21.
MITOSIS IDENTIFICATION THROUGH SELECTIVE MULTISTEP DEEP LEARNING ANALYSIS
Mitosis can be detected using a two step detection method. This type of a detection method may comprise, obtaining a detection output by applying a detection model to the tissue image. Subsequently, for each nucleus in a set of nuclei identified as undergoing mitosis in the detection output, making a certainty determination for that nucleus. Then, for each nucleus from a subset of nuclei, a classification model may be applied to that nucleus based on a relationship between a confidence for that nucleus and a first threshold. An output may then be provided which identifies each nucleus identified in the detection output as undergoing mitosis and for which the confidence is above the first threshold as undergoing mitosis. Additionally, the output may identify each nucleus from the subset of nuclei indicated as undergoing mitosis in the classification result obtained for that nucleus as undergoing mitosis.
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 20/69 - Objets microscopiques, p. ex. cellules biologiques ou pièces cellulaires
22.
MITOSIS IDENTIFICATION USING A GENERATIVE ADVERSARIAL NETWORK
A machine learning model can be trained to add markings to representations of nuclei undergoing mitosis on tissue images. This may include performing a set of training data creation steps, and a set of model training steps. The training data creation steps may include receiving a tissue image comprising a set of representation of nuclei undergoing mitosis, and creating a target image corresponding to the tissue image. The set of model training steps may include providing the tissue image to a generator model, generating an output image based on the tissue image using the generator model, and training the generator model to create improved output images based on differences between the output image and the target image.
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 20/69 - Objets microscopiques, p. ex. cellules biologiques ou pièces cellulaires
09 - Appareils et instruments scientifiques et électriques
10 - Appareils et instruments médicaux
Produits et services
Scientific apparatus and instruments, namely, digital slide systems comprised of microscopes, digital cameras, digital slide scanners for digital image capture and data processing for use in research laboratories; computer software for data and image measuring and processing systems for use with microscopes in research laboratories; computer software for data and image measuring and processing systems for use with microscopes in the medical field. Medical apparatus and instruments, namely, digital slide systems comprised of microscopes for surgical operations, digital cameras, and digital slide scanners for digital image capture and data processing for use in the medical field.
09 - Appareils et instruments scientifiques et électriques
10 - Appareils et instruments médicaux
Produits et services
Scientific apparatus and instruments, namely, digital slide systems comprised of microscopes, digital cameras, digital slide scanners for digital image capture and data processing for use in research laboratories; computer software for data and image measuring and processing systems for use with microscopes in research laboratories; computer software for data and image measuring and processing systems for use with microscopes in the medical field. Medical apparatus and instruments, namely, digital slide systems comprised of microscopes for surgical operations, digital cameras, and digital slide scanners for digital image capture and data processing for use in the medical field.
09 - Appareils et instruments scientifiques et électriques
10 - Appareils et instruments médicaux
Produits et services
Scientific apparatus and instruments, namely, digital slide systems comprised of microscopes, digital cameras, digital slide scanners for digital image capture and data processing for use in research laboratories; computer software for data and image measuring and processing systems for use with microscopes in research laboratories; computer software for data and image measuring and processing systems for use with microscopes in the medical field. Medical apparatus and instruments, namely, digital slide systems comprised of microscopes for surgical operations, digital cameras, and digital slide scanners for digital image capture and data processing for use in the medical field.
A digital pathology scanning apparatus is configured to initiate a rescan of a portion of a sample responsive to detecting a mechanical vibration during image acquisition that exceeds a predetermined threshold. The digital pathology scanning apparatus includes a plurality of sensors and a processor that analyzes sensor data received during movement of a scanning stage supporting a sample during image acquisition. The processor is configured to identify a mechanical vibration imparted on the scanning stage during image acquisition and determine if the mechanical vibration exceeds a predetermined threshold. If the predetermined threshold is exceeded, the processor is configured to initiate a rescan of the portion of the sample being scanned at the time of the mechanical vibration.
H04N 23/68 - Commande des caméras ou des modules de caméras pour une prise de vue stable de la scène, p. ex. en compensant les vibrations du boîtier de l'appareil photo
G01P 13/00 - Indication ou enregistrement de l'existence ou de l'absence d'un mouvementIndication ou enregistrement de la direction d'un mouvement
H04N 3/02 - Détails des dispositifs de balayage des systèmes de télévisionLeur combinaison avec la production des tensions d'alimentation par des moyens optiques-mécaniques uniquement
H04N 23/67 - Commande de la mise au point basée sur les signaux électroniques du capteur d'image
H04N 25/711 - Registres à report et intégration [TDI]Registres à décalage TDI
09 - Appareils et instruments scientifiques et électriques
10 - Appareils et instruments médicaux
Produits et services
Automated digital scanning system integrating optical microscopy, motorized sample positioning, digital image capture, data processing, manipulation and display for use in scanning and digitizing microscope samples in research and clinical laboratory environments, comprised of a microscope, digital camera, microscope slide scanner for digital image capture, and downloadable computer software for digitizing microscope slides, analyzing and storing images, managing and analyzing information relating to scanned microscope samples, and tracking histological and cytological specimen locations, all of the foregoing not for medical use apart from medical research; image analysis devices, namely, scanners for capturing images for analysis for use in medical research and clinical laboratory environments, all of the foregoing not for medical use apart from medical research; electronic image recording, image storing and image representing devices, namely, digital cameras; Downloadable and recorded computer operating software for image analysis and image storage devices; Downloadable and recorded computer operating software for automated digital scanning systems; Downloadable and recorded computer software for digitizing microscope slides for viewing, integration with other data, management, and analysis, all in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; Downloadable and recorded computer software for managing digital microscope slide information, digitizing glass microscope slides into diagnostic quality images displayed in context with reports, case histories and other associated documents or data, and for optionally cross-linking and concurrently viewing microscope slide information and images for use in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology; Downloadable and recorded computer software for tracking the location of histological and cytological specimens; Downloadable and recorded computer software for image data storage and archiving on local servers or networks for use in research and clinical environments Medical diagnostic apparatus for the analysis of biological samples; medical apparatus and instruments, namely, digital slide systems incorporating microscopes, digital cameras, digital slide scanners, equipped with digital image capture and data processing devices for medical and clinical diagnostic purposes in the fields of virtual microscopy, digital pathology, digital hematology and medical information technology
28.
SYSTEM AND METHOD FOR QUALITY ASSURANCE OF PIXEL PIPELINE
Methods and systems method for determining quality of an image after a system configuration change. A method includes receiving an indication of a configuration update of an imaging system, processing a test image using the image display system to generate updated test image pixel data for display on the imaging system, determining if the updated test image pixel data is different than the ground truth pixel data of the test image by more than a quality threshold, and in response to the updated test image pixel data being different than the ground truth pixel data of the test image by more than the quality threshold, generate in indicator that the configuration change adversely affected the image generation properties of the imaging system.
A computer apparatus and method for identifying and visualizing tumors in a histological image and measuring a tumor margin are provided. A CNN is used to classify pixels in the image according to whether they are determined to relate to nontumorous tissue, or one or more classes for tumorous tissue. Segmentation is carried out based on the CNN results to generate a mask that marks areas occupied by individual tumors. Summary statistics for each tumor are computed and supplied to a filter which edits the segmentation mask by filtering out tumors deemed to be insignificant. Optionally, the tumors that pass the filter may be ranked according to the summary statistics, for example in order of clinical relevance or by a sensible order of review for a pathologist. A visualization application can then display the histological image having regard to the segmentation mask, summary statistics and/or ranking. Tumor masses extracted by resection are painted with an ink to highlight its surface region. The CNN is trained to distinguish ink and no-ink tissue as well as tumor and no-tumor tissue. The CNN is applied to the histological image to generate an output image whose pixels are assigned to the tissue classes. Tumor margin status of the tissue section is determined by the presence or absence of tumor-and-ink classified pixels. Tumor margin involvement and tumor margin distance are determined by computing additional parameters based on classification-specified inter-pixel distance parameters.
Real-time focusing in a slide-scanning system. In an embodiment, focus points are added to 500 an initialized focus map while acquiring a plurality of image stripes of a sample on a glass slide. For each image stripe, a plurality of frames, collectively representing the image stripe, may be acquired using both an imaging line-scan camera and a tilted focusing line-scan camera. Focus points, representing positions of best focus for trusted frames, are added to the focus map. Outlying focus points are removed from the focus map. In some cases, one or more image stripes may be reacquired. Finally, the image stripes are assembled into a composite image of the sample.
G02B 21/36 - Microscopes aménagés pour la photographie ou la projection
H04N 3/06 - Détails des dispositifs de balayage des systèmes de télévisionLeur combinaison avec la production des tensions d'alimentation par des moyens optiques-mécaniques uniquement comportant une lentille mobile ou autre réfracteur
H04N 23/90 - Agencement de caméras ou de modules de caméras, p. ex. de plusieurs caméras dans des studios de télévision ou des stades de sport
31.
APPARATUS AND METHOD FOR TRAINING OF MACHINE LEARNING MODELS USING ANNOTATED IMAGE DATA FOR PATHOLOGY IMAGING
Features are disclosed for training a machine learning model to identify objects in histological images. A system may obtain an image and determine a number of objects in the image. For example, the system may determine a percentage of objects in the image with a particular object type. Further, the system may determine a weight. The weight may specify a percentage of the image occupied by objects with the particular object type. The system can generate training set data that includes the image, data identifying the number of objects in the image, and the weight. The system can use the training set data to train a machine learning model to predict a number of objects in a different image and a weight. The system can implement the machine learning model based on training the machine learning model.
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
G16H 30/40 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le traitement d’images médicales, p. ex. l’édition
Features are disclosed for rendering an image using a GPU and CPU based rendering pipeline. An imaging system may include a GPU and a CPU that each include a portion of an image renderer. A component of the GPU can process the set of image tiles to generate a texture with a wrapped tile coordinate. A component of the GPU can further store the image data as a level of a texture pyramid. As subsequent image data is received, a component of the GPU can access the texture pyramid to determine previously stored image tiles. A component of the GPU can use the previously stored image tiles in rendering the subsequent image data.
Systems and methods for normalizing image data obtained using multispectral imaging are disclosed. In one aspect, an image analysis apparatus includes an imaging device configured to perform a multispectral scan of a tissue sample to generate image data, a processor, and at least one computer-readable memory. The processor is configured to receive the image data from the imaging device and preprocess the image data to generate a normalization factor based on pixel values of the image data within at least one sub-region of the image data. The processor is also configured to provide the preprocessed image data and the normalization factor as inputs to a machine learning algorithm and determine, based on an output of the machine learning algorithm, whether the image data is indicative of a disease present in the tissue sample.
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
34.
SYSTEM AND METHOD FOR MATCHING OF BLOCK AND SLICE HISTOLOGICAL SAMPLES
Features are disclosed for imaging block and slice samples using an imaging system. The imaging system can link the images by identifiers associated with the block and slice samples. The imaging system can train a machine learning algorithm based on correctly linked images. In some embodiments, the trained machine learning algorithm may include an image analysis module or a convolutional neural network. The imaging system can use the trained machine learning algorithm in order to determine a confidence score of a match between the block and the slice samples. The trained machine learning algorithm can use features of the block and the slice samples such as shape and tissue morphology to determine whether the samples match. In some embodiments, when the confidence score is below a certain threshold, the imaging system can alert a user that the samples may not match.
An input device allows a user to manipulate an image displayed by a user interface (UI) of a computer. The input device includes a housing, a first rotatable control knob supported by the housing, and a second rotatable control knob supported by the housing. The first and second rotatable control knobs allow the user to perform at least zooming and panning manipulations of the image on the UI. The input device can further include a third rotatable control knob and a touch pad. The input device can be configured as a keyboard.
G06F 3/0362 - Dispositifs de pointage déplacés ou positionnés par l'utilisateurLeurs accessoires avec détection des translations ou des rotations unidimensionnelles [1D] d’une partie agissante du dispositif de pointage, p. ex. molettes de défilement, curseurs, boutons, rouleaux ou bandes
G06F 3/04845 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs pour la transformation d’images, p. ex. glissement, rotation, agrandissement ou changement de couleur
G06F 3/02 - Dispositions d'entrée utilisant des interrupteurs actionnés manuellement, p. ex. des claviers ou des cadrans
G06F 3/0354 - Dispositifs de pointage déplacés ou positionnés par l'utilisateurLeurs accessoires avec détection des mouvements relatifs en deux dimensions [2D] entre le dispositif de pointage ou une partie agissante dudit dispositif, et un plan ou une surface, p. ex. souris 2D, boules traçantes, crayons ou palets
36.
HIGH AND LOW FREQUENCY FEATURE MAP GENERATION FOR H&E PATHOLOGY IMAGES
An apparatus and methods for determining features in an image of a Hematoxylin and Eosin (H&E) stained tissue sample. An apparatus can be configured to apply a machine learning model to the H&E stained tissue sample image to determine features in the image. Applying the machine learning model can include performing convolution operations on the H&E stained tissue sample image to generate a plurality of initial feature maps, applying octave-convolution-first-layer operations on the initial feature maps to generate initial high-frequency feature maps and low-frequency feature maps, applying octave-convolution operations on the high-frequency initial feature maps to generate refined high-frequency feature maps, applying octave-convolution operations on the low-frequency initial feature maps to generate refined low-frequency feature maps, and applying octave-convolution last layer operations on the refined high-frequency feature maps and the refined low-frequency feature maps to produce combined feature maps.
G06V 10/771 - Sélection de caractéristiques, p. ex. sélection des caractéristiques représentatives à partir d’un espace multidimensionnel de caractéristiques
G06T 3/40 - Changement d'échelle d’images complètes ou de parties d’image, p. ex. agrandissement ou rétrécissement
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
37.
SYSTEMS AND METHODS FOR CLASSIFICATION OF HISTOPATHOLOGY IMAGES
Systems and methods for classification of histopathology images arc disclosed. In one aspect, an apparatus for detecting a medical condition in a histopathology image includes a hardware memory configured to store executable instructions and a hardware processor in communication with the hardware memory, wherein the executable instructions, when executed by the processor, cause the processor to obtain a plurality of patches at a plurality of magnification levels from the histopathology image, apply a deep learning algorithm to each of the patches, extract, from applying the deep learning algorithm, information representative of a hierarchical relationship that links characteristics of the histopathology image present at one level and another level of the plurality of magnification levels, and identify the medical condition based on the extracted information representative of the hierarchical relationship for characteristics present at the one level and at the another level of the plurality of magnification levels.
G06V 20/69 - Objets microscopiques, p. ex. cellules biologiques ou pièces cellulaires
G06V 10/50 - Extraction de caractéristiques d’images ou de vidéos en effectuant des opérations dans des blocs d’imagesExtraction de caractéristiques d’images ou de vidéos en utilisant des histogrammes, p. ex. l’histogramme de gradient orienté [HoG]Extraction de caractéristiques d’images ou de vidéos en utilisant l’addition des valeurs d’intensité d’imageAnalyse de projection
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/762 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant le regroupement, p. ex. de visages similaires sur les réseaux sociaux
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 10/25 - Détermination d’une région d’intérêt [ROI] ou d’un volume d’intérêt [VOI]
G06V 10/22 - Prétraitement de l’image par la sélection d’une région spécifique contenant ou référençant une formeLocalisation ou traitement de régions spécifiques visant à guider la détection ou la reconnaissance
G06V 10/80 - Fusion, c.-à-d. combinaison des données de diverses sources au niveau du capteur, du prétraitement, de l’extraction des caractéristiques ou de la classification
Systems and methods for determining pixel classification information using images depicting at least a portion of a whole slide image (WSI) of a stained tissue sample. A system can store a first image of the tissue sample at a first resolution, a second image of the tissue sample at a second resolution that is higher than the first resolution, and a third image of the tissue sample at a third resolution that is higher than the second resolution, the first, second, and third images depicting at least a portion of a same area of the tissue sample. The system can include be configured to generate first feature information based on the first image, generate second feature information based on the second image, and determine pixel classification information of at least a portion of the WSI based on the third image, the first feature information and second feature information.
G06T 3/40 - Changement d'échelle d’images complètes ou de parties d’image, p. ex. agrandissement ou rétrécissement
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
39.
SYSTEM AND METHOD FOR SIMILARITY LEARNING IN DIGITAL PATHOLOGY
Systems and methods for similarity learning in digital pathology are provided. In one aspect, an apparatus for generating training image data includes a hardware memory configured to store executable instructions and a hardware processor in communication with the hardware memory, wherein the executable instructions, when executed by the processor, cause the processor to obtain a plurality of histopathology images, classify two or more of the histopathology images as similar or dissimilar, and create a dataset of training image data including the classified histopathology images.
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 10/74 - Appariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques
40.
SYSTEMS AND METHODS FOR MEASURING PROXIMITY OF OBJECTS ACROSS SERIAL SECTIONS OF OVERLAYED STAINED SLIDE PATHOLOGY IMAGES
Determining spatial analysis data in images each depicting a proximate serial tissue section obtained from a tissue sample. The stained tissue sections include markers (object, markers, etc.) that correspond to material in the tissue sample. The images each include data depicting the markers of the stained tissue sections corresponding to the image. The images are registered and “overlayed” to form a representation of the tissue sample such that intra-section and inter-section measurements between markers in the images correspond to measurements of corresponding material in the tissue sample. A process determines intra-section and/or inter-section measurements between locations of data depicting markers in the images, the measurements representing a distance in 3D space between objects in the tissue sample associated with the markers, and the measurements are stored for use in subsequent processing, for example, spatial analysis of the markers.
A power off delay system and method is configured to delay termination of electrical power to a digital pathology device in a power off condition. If the apparatus includes a UPS, the power off delay system and method delays termination of electrical power when a power switch is turned off and when a catastrophic power failure occurs. During the delay of the termination of electrical power, the digital pathology device is configured to control the scanning stage system and the glass slide conveyor system and the slide rack conveyor system to place each of these systems into a known state and position all glass slides into a known position prior to the termination of electrical power to the digital pathology device. This allows the digital pathology device to resume normal operation upon power up.
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
G02B 21/26 - PlatinesMoyens de réglage pour celles-ci
G02B 21/34 - Lames de microscope, p. ex. montage d'échantillons sur des lames de microscope
H02J 9/06 - Circuits pour alimentation de puissance de secours ou de réserve, p. ex. pour éclairage de secours dans lesquels le système de distribution est déconnecté de la source normale et connecté à une source de réserve avec commutation automatique
A slide rack gripper apparatus is provided that simultaneously conveys a plurality of glass slides in the protection of a slide rack within a digital slide scanning apparatus. The slide rack gripper apparatus conveys the plurality of glass slides from a slide rack carousel to a scanning stage for processing. The slide rack gripper includes a first motor attached to a base configured to drive a finger mount attached to the base along a first linear axis. The slide rack gripper apparatus also includes a second motor attached to the finger mount and configured to drive opposing gripper fingers attached to the finger mount along a second linear axis. The second motor is also configured to drive individual gripper fingers along a third linear axis to move the gripper fingers toward each other and away from each other to grasp or release a slide rack.
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer hardware, namely, central processing units,
servers, scanners, monitors and multiple-screen display
monitors, and computer software for digitizing microscope
slides for viewing, integration with other data, management,
and analysis, all in the fields of virtual microscopy,
digital pathology, digital hematology and medical
information technology; automated digital scanning system
integrating optical microscopy, motorized sample
positioning, digital image capture, data processing,
manipulation and display for use in scanning and digitizing
microscope samples in research and clinical environments;
digital slide information management software for digitizing
entire glass microscope slides into diagnostic quality
images displayed in context with reports, case histories and
other associated documents, cross-linked and concurrently
viewable for use in the fields of virtual microscopy,
digital pathology, digital hematology and medical
information technology; computer imaging software for
digitizing, analysis and processing of microscope slides and
associated data; downloadable computer software for
digitizing, analysis, and processing microscope slides and
associated data; downloadable scientific and medical
multimedia data, namely, high resolution digital images of
microscope slides of associated data via the internet. Technical consultation, scientific research services and
custom design of computer hardware and software systems in
the fields of virtual microscopy, digital pathology, digital
hematology and medical information technology; virtual
microscopy services, namely, converting glass microscope
slides to high resolution digital images of slides that can
be viewed, integrated with other associated data, managed
and analyzed; providing temporary use of non-downloadable
computer software for use in database management of
digitized images of microscope slides and other associated
medical information over computer networks, in the fields of
virtual microscopy, digital pathology, digital hematology
and medical information technology.
09 - Appareils et instruments scientifiques et électriques
Produits et services
Automated image analysis computer hardware system comprising
printed circuit boards, hard drives, keyboard, monitors,
digital scanner, video camera and camera stand; computer
software for cellular image and chromosome analysis in the
field of molecular biology and genetic research.
45.
SYSTEM AND METHOD FOR QUALITY ASSURANCE OF PIXEL PIPELINE
Methods and systems method for determining quality of an image after a system configuration change. A method includes receiving an indication of a configuration update of an imaging system, processing a test image using the image display system to generate updated test image pixel data for display on the imaging system, determining if the updated test image pixel data is different than the ground truth pixel data of the test image by more than a quality threshold, and in response to the updated test image pixel data being different than the ground truth pixel data of the test image by more than the quality threshold, generate in indicator that the configuration change adversely affected the image generation properties of the imaging system.
c), each comprising a plurality of pixel sensors. Each line sensor is offset from an adjacent line sensor by a fraction of a length of each pixel sensor, and generates a line image of the same field of view at its respective offset. For each of a plurality of positions on a sample, a processor combines the line images of the same field of view, generated by the plurality of line sensors at their respective offsets, to produce a plurality of subpixels for each of at least a subset of pixels within the line images of the same field of view, and generates an up-sampled line image of the position comprising the plurality of subpixels. Then, the processor combines the up-sampled line images of each of the plurality of positions on the sample into an image.
Real-time autofocus. In an embodiment, a scanning apparatus includes an imaging sensor, a focusing sensor, an objective lens, and processor(s) configured to analyze image data captured by the imaging and focusing sensors, and move the objective lens. Real-time autofocus during scanning of a sample is achieved by determining a true-Z value for the objective lens for a point on a sample and for each of a plurality of regions on the sample. The true-Z values and/or surfaces calculated therefrom are used to determine a predicted-Z value for an unscanned region of the sample. The objective lens is adjusted to the predicted-Z value at the beginning of the unscanned region. After scanning the region, a true-Z value is determined for the region and compared to the predicted-Z value. A rescan of the region is initiated if the comparison exceeds a predetermined threshold.
A power off delay system and method is configured to delay termination of electrical power to a digital pathology device in a power off condition. If the apparatus includes a UPS, the power off delay system and method delays termination of electrical power when a power switch is turned off and when a catastrophic power failure occurs. During the delay of the termination of electrical power, the digital pathology device is configured to control the scanning stage system and the glass slide conveyor system and the slide rack conveyor system to place each of these systems into a known state and position all glass slides into a known position prior to the termination of electrical power to the digital pathology device. This allows the digital pathology device to resume normal operation upon power up.
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
G02B 21/26 - PlatinesMoyens de réglage pour celles-ci
G02B 21/34 - Lames de microscope, p. ex. montage d'échantillons sur des lames de microscope
H02J 9/06 - Circuits pour alimentation de puissance de secours ou de réserve, p. ex. pour éclairage de secours dans lesquels le système de distribution est déconnecté de la source normale et connecté à une source de réserve avec commutation automatique
A stall detection system is provided that determines if a glass slide in motion during an automated process is at risk for being damaged and stops motion in the event of an unacceptable risk of damage. The system includes one or more motors configured to move a glass slide (directly or indirectly). The motors are configured to generate a load resistance value. The system includes one or more processors that monitor the load resistance value of a motor during motion and compares the load resistance value to a predetermined threshold resistance value to determine the risk of a glass slide being damaged. The predetermined threshold resistance value may correspond to a risk of slide breakage in response to a force applied to any surface of the slide, or a risk of losing a controlling grip on a slide rack, or a risk of a motor skipping a motor step.
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
Image viewing in digital pathology using eye-tracking. In an embodiment, a position of a user's gaze on a graphical user interface, comprising at least a portion of a digital slide image within a macro view, is repeatedly detected based on an output from an eye-tracking device. After detecting a change of the user's gaze from a first position to a second position on the graphical user interface, a view of the digital slide image within the macro view is automatically panned based on the second position, so as to move a position on the digital slide image that corresponds to the second position on the graphical user interface toward a center of the macro view.
G06V 40/18 - Caractéristiques de l’œil, p. ex. de l’iris
G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
G16H 40/67 - TIC spécialement adaptées à la gestion ou à l’administration de ressources ou d’établissements de santéTIC spécialement adaptées à la gestion ou au fonctionnement d’équipement ou de dispositifs médicaux pour le fonctionnement d’équipement ou de dispositifs médicaux pour le fonctionnement à distance
G16H 30/20 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le maniement d’images médicales, p. ex. DICOM, HL7 ou PACS
G06F 3/0485 - Défilement ou défilement panoramique
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
51.
DIGITAL PATHOLOGY APPARATUS HOUSING WITH RAIL SYSTEM, SPEAKERLESS AUDIO SYSTEM, AND ELECTROMAGNETIC RADIATION SHIELDING
A digital pathology apparatus includes a housing with a rail system that allows the housing to slide off of the apparatus to expose the internal elements of the apparatus for easy maintenance. The housing includes a latch and sensor system that securely latches the housing in the closed position and senses when the housing is opened so that the moving parts of the apparatus can be safely stopped to avoid potential injury. The housing also includes electromagnetic shielding on a minimal portion of its interior surface to reduce electromagnetic radiation emanating from the apparatus. The digital pathology apparatus also includes a speakerless audio system that engages with a portion of the interior surface of the housing that is not covered with electromagnetic shielding. The speakerless audio system provides an audio user interface while maintaining a contiguous surface on the housing to cover the digital pathology apparatus.
Control processes for a slide-scanning system comprising a carousel with a plurality of rack slots configured to receive slide racks via an exposed portion of the scanning system. In an embodiment, initializing the scanning system comprises automatically homing back-end and front-end components, wherein the front-end components comprise the carousel. An inventory of all slide racks in the carousel is automatically generated. If any slide rack was being processed by any back-end components, the slide rack is automatically unloaded into a corresponding rack slot. In addition, the carousel is automatically positioned to expose a starting subset of the rack slots within the exposed portion. This starting subset may comprise a maximum segment of adjacent empty rack slots.
G01V 8/20 - Détection, p. ex. en utilisant des barrières de lumière en utilisant plusieurs émetteurs ou récepteurs
G02B 21/34 - Lames de microscope, p. ex. montage d'échantillons sur des lames de microscope
G01N 35/02 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet en utilisant une série de récipients à échantillons déplacés par un transporteur passant devant un ou plusieurs postes de traitement ou d'analyse
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
53.
APPARATUS AND METHOD FOR TRAINING OF MACHINE LEARNING MODELS USING ANNOTATED IMAGE DATA FOR PATHOLOGY IMAGING
Features are disclosed for training a machine learning model to identify objects in histological images. A system may obtain an image and determine a number of objects in the image. For example, the system may determine a percentage of objects in the image with a particular object type. Further, the system may determine a weight. The weight may specify a percentage of the image occupied by objects with the particular object type. The system can generate training set data that includes the image, data identifying the number of objects in the image, and the weight. The system can use the training set data to train a machine learning model to predict a number of objects in a different image and a weight. The system can implement the machine learning model based on training the machine learning model.
G16H 50/70 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour extraire des données médicales, p. ex. pour analyser les cas antérieurs d’autres patients
G16H 30/40 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le traitement d’images médicales, p. ex. l’édition
54.
Graphical user interface for slide-scanner control
Graphical user interface for managing a workflow of a slide scanning system. In an embodiment, the graphical user interface comprises a graphical representation of a carousel used by the scanning system. The graphical representation of the carousel comprises a graphical representation of each of a plurality of rack slots, configured to receive slide racks. The graphical representation of the carousel indicates a position of the carousel, and the graphical representation of each of the plurality of rack slots indicates a status of the represented rack slot and/or a slide rack within the represented rack slot.
G06F 3/048 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI]
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
G01N 35/02 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet en utilisant une série de récipients à échantillons déplacés par un transporteur passant devant un ou plusieurs postes de traitement ou d'analyse
G06F 3/0488 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] utilisant des caractéristiques spécifiques fournies par le périphérique d’entrée, p. ex. des fonctions commandées par la rotation d’une souris à deux capteurs, ou par la nature du périphérique d’entrée, p. ex. des gestes en fonction de la pression exercée enregistrée par une tablette numérique utilisant un écran tactile ou une tablette numérique, p. ex. entrée de commandes par des tracés gestuels
55.
User-assisted iteration of cell image segmentation
A segmentation of cell image data obtains cell segmentation data for the nuclei, cytoplasm and cell membranes, which are displayed on an image pane. A data pane is also displayed which contains a table with rows specific to cells and columns specific to cell attributes. In an editing session, a user can select cells for deletion either from the data pane or the image pane. Responsive to a selection via the data pane, the image pane is updated and responsive to a selection via the image pane, the data pane is updated. At any time, the user can command a re-segmentation taking account of the edits, which starts from a version of the previous nuclear segmentation data which has been edited to remove data relating to cells selected for deletion and then from that determines the cytoplasm and cell membrane segmentation data.
Features are disclosed for rendering an image using a GPU and CPU based rendering pipeline. An imaging system may include a GPU and a CPU that each include a portion of an image renderer. A component of the GPU can process the set of image tiles to generate a texture with a wrapped tile coordinate. A component of the GPU can further store the image data as a level of a texture pyramid. As subsequent image data is received, a component of the GPU can access the texture pyramid to determine previously stored image tiles. A component of the GPU can use the previously stored image tiles in rendering the subsequent image data.
G09G 5/00 - Dispositions ou circuits de commande de l'affichage communs à l'affichage utilisant des tubes à rayons cathodiques et à l'affichage utilisant d'autres moyens de visualisation
G06T 1/20 - Architectures de processeursConfiguration de processeurs p. ex. configuration en pipeline
09 - Appareils et instruments scientifiques et électriques
Produits et services
Automated image analysis computer hardware system comprising printed circuit boards, hard drives, keyboard, monitors, digital scanner, video camera and camera stand; downloadable and recorded computer software for cellular image and chromosome analysis in the field of molecular biology and genetic research
58.
SYSTEM AND METHOD FOR NORMALIZING IMAGE DATA OBTAINED USING MULTISPECTRAL IMAGING
Systems and methods for normalizing image data obtained using multispectral imaging are disclosed. In one aspect, an image analysis apparatus includes an imaging device configured to perform a multispectral scan of a tissue sample to generate image data, a processor, and at least one computer-readable memory. The processor is configured to receive the image data from the imaging device and preprocess the image data to generate a normalization factor based on pixel values of the image data within at least one sub-region of the image data. The processor is also configured to provide the preprocessed image data and the normalization factor as inputs to a machine learning algorithm and determine, based on an output of the machine learning algorithm, whether the image data is indicative of a disease present in the tissue sample.
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
59.
SYSTEM AND METHOD FOR MATCHING OF BLOCK AND SLICE HISTOLOGICAL SAMPLES
Features are disclosed for imaging block and slice samples using an imaging system. The imaging system can link the images by identifiers associated with the block and slice samples. The imaging system can train a machine learning algorithm based on correctly linked images. In some embodiments, the trained machine learning algorithm may include an image analysis module or a convolutional neural network. The imaging system can use the trained machine learning algorithm in order to determine a confidence score of a match between the block and the slice samples. The trained machine learning algorithm can use features of the block and the slice samples such as shape and tissue morphology to determine whether the samples match. In some embodiments, when the confidence score is below a certain threshold, the imaging system can alert a user that the samples may not match.
An input device allows a user to manipulate an image displayed by a user interface (UI) of a computer. The input device includes a housing, a first rotatable control knob supported by the housing, and a second rotatable control knob supported by the housing. The first and second rotatable control knobs allow the user to perform at least zooming and panning manipulations of the image on the UI. The input device can further include a third rotatable control knob and a touch pad. The input device can be configured as a keyboard.
G06F 3/02 - Dispositions d'entrée utilisant des interrupteurs actionnés manuellement, p. ex. des claviers ou des cadrans
G06F 3/0362 - Dispositifs de pointage déplacés ou positionnés par l'utilisateurLeurs accessoires avec détection des translations ou des rotations unidimensionnelles [1D] d’une partie agissante du dispositif de pointage, p. ex. molettes de défilement, curseurs, boutons, rouleaux ou bandes
G06F 3/0485 - Défilement ou défilement panoramique
A slide rack inventory and reinsertion system for use with a digital slide scanning apparatus is provided that determines, prior to scanning of glass slides in a slide rack, a status of each slot in the slide rack as properly occupied, improperly occupied, or empty. The system also determines whether a slide that has been removed from the slide rack for processing has been properly reinserted into the slide rack.
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
G01N 21/84 - Systèmes spécialement adaptés à des applications particulières
G01V 8/12 - Détection, p. ex. en utilisant des barrières de lumière en utilisant un émetteur et un récepteur
Systems and methods for capturing a digital image of a slide using an imaging line sensor and a focusing line sensor. In an embodiment, a beam-splitter is optically coupled to an objective lens and configured to receive one or more images of a portion of a sample through the objective lens. The beam-splitter simultaneously provides a first portion of the one or more images to the focusing sensor and a second portion of the one or more images to the imaging sensor. A processor controls the stage and/or objective lens such that each portion of the one or more images is received by the focusing sensor prior to it being received by the imaging sensor. In this manner, a focus of the objective lens can be controlled using data received from the focusing sensor prior to capturing an image of a portion of the sample using the imaging sensor.
Physical calibration slide comprising a plurality of etched features. The etched features may comprise two or more of a slanted Ronchi ruling feature comprising at least one set of parallel lines that are slanted with respect to a long and short axis of the slide, a straight Ronchi ruling feature comprising at least one set of parallel lines that are parallel to either the long or short axis, a star target feature comprising a circle with a plurality of wedge pairs, a crosshair feature comprising at least one crosshair, a clear area, a letter-O feature comprising a circle, a resolution target feature comprising one or more resolution targets, a bullseye feature comprising a two-dimensional array of bullseyes, a triangle feature comprising at least one isosceles triangle, or a symmetric corers feature comprising two symmetric sets of geometric shapes arranged in an L-shape.
Real-time focusing in a slide-scanning system. In an embodiment, focus points are added to an initialized focus map while acquiring a plurality of image stripes of a sample on a glass slide. For each image stripe, a plurality of frames, collectively representing the image stripe, may be acquired using both an imaging line-scan camera and a tilted focusing line-scan camera. Focus points, representing positions of best focus for trusted frames, are added to the focus map. Outlying focus points are removed from the focus map. In some cases, one or more image stripes may be reacquired. Finally, the image stripes are assembled into a composite image of the sample.
G02B 21/36 - Microscopes aménagés pour la photographie ou la projection
H04N 3/06 - Détails des dispositifs de balayage des systèmes de télévisionLeur combinaison avec la production des tensions d'alimentation par des moyens optiques-mécaniques uniquement comportant une lentille mobile ou autre réfracteur
H04N 23/90 - Agencement de caméras ou de modules de caméras, p. ex. de plusieurs caméras dans des studios de télévision ou des stades de sport
H04N 23/56 - Caméras ou modules de caméras comprenant des capteurs d'images électroniquesLeur commande munis de moyens d'éclairage
65.
ARTIFICIAL INTELLIGENCE PROCESSING SYSTEM AND AUTOMATED PRE-DIAGNOSTIC WORKFLOW FOR DIGITAL PATHOLOGY
A digital pathology system comprising an AI processing module configured to invoke an instance of an AI processing application for processing image data from a histological image and an application module configured to invoke an instance of an application operable to perform an image processing task on a histological image associated with a patient record, wherein the image processing task includes an AI element. The application creates processing jobs to handle the AI elements of its task which are handled by the AI processing module. The AI processing module may be a CNN that processes a histological image to identify tumors by classifying image pixels into one of multiple tissue classes of tumorous or non-tumorous tissue. A test ordering module automatically determines based on identified tissue classes whether additional tests should be performed on the tissue sample. For each additional test, an order is automatically created and submitted. Advantageously, upon first review by a pathologist, the patient record includes the histological image and results from the automatically ordered additional tests.
G16H 30/40 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le traitement d’images médicales, p. ex. l’édition
G16H 30/20 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le maniement d’images médicales, p. ex. DICOM, HL7 ou PACS
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
G16H 10/60 - TIC spécialement adaptées au maniement ou au traitement des données médicales ou de soins de santé relatives aux patients pour des données spécifiques de patients, p. ex. pour des dossiers électroniques de patients
A computer apparatus and method for identifying and visualizing tumors in a histological image and measuring a tumor margin are provided. A CNN is used to classify pixels in the image according to whether they are determined to relate to non-tumorous tissue, or one or more classes for tumorous tissue. Segmentation is carried out based on the CNN results to generate a mask that marks areas occupied by individual tumors. Summary statistics for each tumor are computed and supplied to a filter which edits the segmentation mask by filtering out tumors deemed to be insignificant. Optionally, the tumors that pass the filter may be ranked according to the summary statistics, for example in order of clinical relevance or by a sensible order of review for a pathologist. A visualization application can then display the histological image having regard to the segmentation mask, summary statistics and/or ranking. Tumor masses extracted by resection are painted with an ink to highlight its surface region. The CNN is trained to distinguish ink and no-ink tissue as well as tumor and no-tumor tissue. The CNN is applied to the histological image to generate an output image whose pixels are assigned to the tissue classes. Tumor margin status of the tissue section is determined by the presence or absence of tumor-and-ink classified pixels. Tumor margin involvement and tumor margin distance are determined by computing additional parameters based on classification-specified inter-pixel distance parameters.
A CNN is applied to a histological image to identify areas of interest. The CNN classifies pixels according to relevance classes including one or more classes indicating levels of interest and at least one class indicating lack of interest. The CNN is trained on a training data set including data which has recorded how pathologists have interacted with visualizations of histological images. In the trained CNN, the in-terest-based pixel classification is used to generate a segmentation mask that defines areas of interest. The mask can be used to indicate where in an image clinically relevant features may be located. Further, it can be used to guide variable data compression of the histological image. Moreover, it can be used to control loading of image data in either a client-server model or within a memory cache policy. Furthermore, a histological image of a tissue sample of a tissue type that has been treated with a test compound is image processed in order to detect areas where toxic reactions to the test compound may have occurred. An autoencoder is trained with a training data set comprising histological images of tissue samples which are of the given tissue type, but which have not been treated with the test compound. The trained autoencoder is applied to detect tissue areas by their deviation from the normal variation seen in that tissue type as learnt by the training process, and so build up a toxicity map of the image. The toxicity map can then be used to direct a toxicological pathologist to examine the areas identified by the autoencoder as lying outside the normal range of heterogeneity for the tissue type. This makes the pathologist's review quicker and more reliable. The toxicity map can also be overlayed with the segmentation mask indicating areas of interest. When an area of interest and an area identified as lying outside the normal range of heterogeneity for the tissue type, and increased confidence score is applied to the overlapping area.
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 10/764 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant la classification, p. ex. des objets vidéo
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 20/69 - Objets microscopiques, p. ex. cellules biologiques ou pièces cellulaires
G16H 80/00 - TIC spécialement adaptées pour faciliter la communication entre les professionnels de la santé ou les patients, p. ex. pour le diagnostic collaboratif, la thérapie collaborative ou la surveillance collaborative de l’état de santé
Image viewing in digital pathology using eye-tracking. In an embodiment, a position of a user's gaze on a graphical user interface, comprising at least a portion of a digital slide image within a macro view, is repeatedly detected based on an output from an eye-tracking device. After detecting a change of the user's gaze from a first position to a second position on the graphical user interface, a view of the digital slide image within the macro view is automatically panned based on the second position, so as to move a position on the digital slide image that corresponds to the second position on the graphical user interface toward a center of the macro view.
G06F 3/01 - Dispositions d'entrée ou dispositions d'entrée et de sortie combinées pour l'interaction entre l'utilisateur et le calculateur
G16H 40/67 - TIC spécialement adaptées à la gestion ou à l’administration de ressources ou d’établissements de santéTIC spécialement adaptées à la gestion ou au fonctionnement d’équipement ou de dispositifs médicaux pour le fonctionnement d’équipement ou de dispositifs médicaux pour le fonctionnement à distance
G16H 30/20 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le maniement d’images médicales, p. ex. DICOM, HL7 ou PACS
G06F 3/0485 - Défilement ou défilement panoramique
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
69.
Digital pathology apparatus display screen with graphical user interface
A fixed reference edge system that guides a glass slide from a slot of a slide rack onto a scanning stage and guides the glass slide from the scanning stage into the slot of the slide rack. In an embodiment, the fixed reference edge has a first side that is parallel to a side of the slot of the slide rack. The system comprises an assembly that includes a push bar configured to push the slide from the slot onto the scanning stage, and a pull bar configured to pull the slide from the scanning stage into the slot of the slide rack. When the slide is pulled into the slide rack, the long edge of the slide is pressed against the first side of the fixed reference edge to maintain a parallel orientation between the slide and the slot of the slide rack.
G02B 21/26 - PlatinesMoyens de réglage pour celles-ci
G01N 1/02 - Dispositifs pour prélever des échantillons
G02B 21/36 - Microscopes aménagés pour la photographie ou la projection
B65G 49/06 - Systèmes transporteurs caractérisés par leur utilisation à des fins particulières, non prévus ailleurs pour des matériaux ou objets fragiles ou dommageables pour des feuilles fragiles, p. ex. en verre
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
A digital slide scanning apparatus slide rack carousel allows continuous loading and unloading of slide racks into the carousel while the digital slide scanning apparatus is simultaneously digitizing glass slides. The slide rack carousel includes a base having an interior portion of its upper surface at an angle. The slide rack carousel also includes plural rack spacers extending upward from the base and adjacent rack spacers define a rack slot. Each rack spacer also includes a rack stopper on each side such that adjacent rack spacers have rack stoppers facing each other. The rack stoppers prevent a slide rack from moving further toward the center of the carousel than desired.
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
G01N 35/02 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet en utilisant une série de récipients à échantillons déplacés par un transporteur passant devant un ou plusieurs postes de traitement ou d'analyse
A digital slide scanning apparatus includes a safety light curtain that operates to disable the motor that rotates the carousel when the presence of an object (e.g., the fingers of an operator) is detected within a predetermined area of the carousel. The light curtain also operates to disable the motor that rotates the carousel when an improperly positioned glass slide or slide rack is detected. The digital slide scanning apparatus also includes a multi-color status indicator for each rack slot that indicates the rack slot location of an improperly positioned glass slide or slide rack.
G01N 1/00 - ÉchantillonnagePréparation des éprouvettes pour la recherche
G01N 35/02 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet en utilisant une série de récipients à échantillons déplacés par un transporteur passant devant un ou plusieurs postes de traitement ou d'analyse
B01L 3/00 - Récipients ou ustensiles pour laboratoires, p. ex. verrerie de laboratoireCompte-gouttes
F16P 3/14 - Dispositifs de sécurité agissant en conjonction avec la commande ou le fonctionnement d'une machineCommandes exigeant l'emploi simultané de plusieurs parties du corps humain avec dispositifs, p. ex. des éléments sensibles, qui agissent sur la commande ou le fonctionnement de la machine lorsqu'une partie du corps humain se trouve dans ou près de la zone de danger les dispositifs étant des cellules photo-électriques ou d'autres dispositifs sensibles sans contact mécanique
B01L 9/00 - Dispositifs de supportDispositifs de serrage
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
A slide rack clamp apparatus that secures a slide rack in a digital slide scanning apparatus. In an embodiment, the slide rack clamp apparatus includes an upper clamp and a lower clamp. Each clamp comprises one or more clamp projections, which are configured to engage one or more recesses in engagement surfaces of a plurality of different slide racks from different manufacturers. The lower clamp is driven by a motor along a linear axis to engage the lower clamp projections with the one or more slide rack recesses of the bottom surface of the slide rack. The motor drives the lower clamp and the engaged slide rack upward to engage the one or more slide rack recesses of the top surface of the slide rack with the clamp projections of the upper clamp to fully engage the slide rack between the upper clamp and the lower clamp.
G01N 35/10 - Dispositifs pour transférer les échantillons vers, dans ou à partir de l'appareil d'analyse, p. ex. dispositifs d'aspiration, dispositifs d'injection
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
Subpixel line scanning. A slide scanning device comprises a plurality of line sensors (112a, 112b, 112c), each comprising a plurality of pixel sensors. Each line sensor is offset from an adjacent line sensor by a fraction of a length of each pixel sensor, and generates a line image of the same field of view at its respective offset. For each of a plurality of positions on a sample, a processor combines the line images of the same field of view, generated by the plurality of line sensors at their respective offsets, to produce a plurality of subpixels for each of at least a subset of pixels within the line images of the same field of view, and generates an up-sampled line image of the position comprising the plurality of subpixels. Then, the processor combines the up-sampled line images of each of the plurality of positions on the sample into an image.
Real-time autofocus. In an embodiment, a scanning apparatus includes an imaging sensor, a focusing sensor, an objective lens, and processor(s) configured to analyze image data captured by the imaging and focusing sensors, and move the objective lens. Real-time autofocus during scanning of a sample is achieved by determining a true-Z value for the objective lens for a point on a sample and for each of a plurality of regions on the sample. The true-Z values and/or surfaces calculated therefrom are used to determine a predicted-Z value for an unscanned region of the sample. The objective lens is adjusted to the predicted-Z value at the beginning of the unscanned region. After scanning the region, a true-Z value is determined for the region and compared to the predicted-Z value. A rescan of the region is initiated if the comparison exceeds a predetermined threshold.
G06T 7/50 - Récupération de la profondeur ou de la forme
H04N 5/372 - Capteurs à dispositif à couplage de charge [CCD]; Registres d'intégration à temps de retard [TDI] ou registres à décalage spécialement adaptés au capteur SSIS
Systems and methods for capturing a digital image of a slide using an imaging line sensor and a focusing line sensor. In an embodiment, a beam-splitter is optically coupled to an objective lens and configured to receive one or more images of a portion of a sample through the objective lens. The beam-splitter simultaneously provides a first portion of the one or more images to the focusing sensor and a second portion of the one or more images to the imaging sensor. A processor controls the stage and/or objective lens such that each portion of the one or more images is received by the focusing sensor prior to it being received by the imaging sensor. In this manner, a focus of the objective lens can be controlled using data received from the focusing sensor prior to capturing an image of a portion of the sample using the imaging sensor.
A segmentation of cell image data obtains cell segmentation data for the nuclei, cytoplasm and cell membranes, which are displayed on an image pane. A data pane is also displayed which contains a table with rows specific to cells and columns specific to cell attributes. In an editing session, a user can select cells for deletion either from the data pane or the image pane. Responsive to a selection via the data pane, the image pane is updated and responsive to a selection via the image pane, the data pane is updated. At any time, the user can command a re-segmentation taking account of the edits, which starts from a version of the previous nuclear segmentation data which has been edited to remove data relating to cells selected for deletion and then from that determines the cytoplasm and cell membrane segmentation data.
A slide rack inventory and reinsertion system for use with a digital slide scanning apparatus is provided that determines, prior to scanning of glass slides in a slide rack, a status of each slot in the slide rack as properly occupied, improperly occupied, or empty. The system also determines whether a slide that has been removed from the slide rack for processing has been properly reinserted into the slide rack.
G01V 8/12 - Détection, p. ex. en utilisant des barrières de lumière en utilisant un émetteur et un récepteur
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
G01N 21/84 - Systèmes spécialement adaptés à des applications particulières
A digital scanning apparatus is provided that includes imaging and focusing sensors and a processor to analyze the image data captured by the imaging and focusing sensors and adjust the focus of the scanning apparatus in real time during a scanning operation. The individual pixels of the imaging sensor are all in the same image plane with respect to the optical path of the digital scanning apparatus. The individual pixels of the focusing sensor are each in a different image plane with respect to the optical path, and one pixel of the focusing sensor is on the same image plane as the image sensor. The processor analyzes image data from the imaging sensor and the focusing sensor and determines a distance and direction to adjust the relative position of an objective lens and a stage of the digital scanning apparatus to achieve optimal focus during the scanning operation.
G02B 7/38 - Systèmes pour la génération automatique de signaux de mise au point utilisant des techniques liées à la netteté de l'image mesurée en différents points de l'axe optique
G02B 21/26 - PlatinesMoyens de réglage pour celles-ci
G02B 7/09 - Montures, moyens de réglage ou raccords étanches à la lumière pour éléments optiques pour lentilles avec mécanisme de mise au point ou pour faire varier le grossissement adaptés pour la mise au point automatique ou pour faire varier le grossissement de façon automatique
G02B 21/36 - Microscopes aménagés pour la photographie ou la projection
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
80.
Low resolution slide imaging and slide label imaging and high resolution slide imaging using dual optical paths and a single imaging sensor
A digital pathology imaging apparatus includes a single line scan camera sensor optically coupled with first and second optical paths. In a first embodiment, transmission mode illumination and oblique mode illumination are simultaneously used during a single stage movement that captures a low resolution macro image of the entire sample area and the entire label area of the slide via the first optical path. In a second embodiment, transmission mode illumination is used during a first stage movement that captures a low resolution macro image of at least the entire sample area via the first optical path and oblique mode illumination is used during a second stage movement that captures a low resolution macro image of at least the entire label area via the first optical path.
Color calibration for digital pathology is provided. A standard glass slide is prepared with a specimen having zero or more stains. The specimen is scanned a first time using a hyperspectral imaging system to produce a first digital image having XYZ color values. The specimen is scanned a second time using a digital pathology imaging system to produce a second digital image having RGB color values. The first and second digital images are then registered against each other to align the digital image data. Individual pixels of the first and second images may be combined in the registration process so that the first and second digital images have substantially similar pixel sizes. A lookup table is generated to associate XYZ color values to RGB color values. Once the lookup table has been generated, it can be used to present RGB color on a display using the corresponding XYZ color.
G06T 7/80 - Analyse des images capturées pour déterminer les paramètres de caméra intrinsèques ou extrinsèques, c.-à-d. étalonnage de caméra
G06T 7/33 - Détermination des paramètres de transformation pour l'alignement des images, c.-à-d. recalage des images utilisant des procédés basés sur les caractéristiques
G06T 7/90 - Détermination de caractéristiques de couleur
G06V 10/75 - Organisation de procédés de l’appariement, p. ex. comparaisons simultanées ou séquentielles des caractéristiques d’images ou de vidéosApproches-approximative-fine, p. ex. approches multi-échellesAppariement de motifs d’image ou de vidéoMesures de proximité dans les espaces de caractéristiques utilisant l’analyse de contexteSélection des dictionnaires
G01J 3/46 - Mesure de couleurDispositifs de mesure de couleur, p. ex. colorimètres
G01J 3/50 - Mesure de couleurDispositifs de mesure de couleur, p. ex. colorimètres en utilisant des détecteurs électriques de radiations
G02B 21/32 - Micromanipulateurs combinés par construction avec des microscopes
G01N 21/27 - CouleurPropriétés spectrales, c.-à-d. comparaison de l'effet du matériau sur la lumière pour plusieurs longueurs d'ondes ou plusieurs bandes de longueurs d'ondes différentes en utilisant la détection photo-électrique
G02B 21/36 - Microscopes aménagés pour la photographie ou la projection
G06T 3/00 - Transformations géométriques de l'image dans le plan de l'image
G06T 3/40 - Changement d'échelle d’images complètes ou de parties d’image, p. ex. agrandissement ou rétrécissement
Real-time focusing in a slide-scanning system. In an embodiment, focus points are added to an initialized focus map while acquiring a plurality of image stripes of a sample on a glass slide. For each image stripe, a plurality of frames, collectively representing the image stripe, may be acquired using both an imaging line-scan camera and a tilted focusing line-scan camera. Focus points, representing positions of best focus for trusted frames, are added to the focus map. Outlying focus points are removed from the focus map. In some cases, one or more image stripes may be reacquired. Finally, the image stripes are assembled into a composite image of the sample.
G02B 21/36 - Microscopes aménagés pour la photographie ou la projection
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
H04N 5/369 - Transformation d'informations lumineuses ou analogues en informations électriques utilisant des capteurs d'images à l'état solide [capteurs SSIS] circuits associés à cette dernière
G02B 7/38 - Systèmes pour la génération automatique de signaux de mise au point utilisant des techniques liées à la netteté de l'image mesurée en différents points de l'axe optique
G03B 13/36 - Systèmes de mise au point automatique
H04N 5/232 - Dispositifs pour la commande des caméras de télévision, p.ex. commande à distance
Physical calibration slide comprising a plurality of etched features. The etched features may comprise two or more of a slanted Ronchi ruling feature comprising at least one set of parallel lines that are slanted with respect to a long and short axis of the slide, a straight Ronchi ruling feature comprising at least one set of parallel lines that are parallel to either the long or short axis, a star target feature comprising a circle with a plurality of wedge pairs, a crosshair feature comprising at least one crosshair, a clear area, a letter-O feature comprising a circle, a resolution target feature comprising one or more resolution targets, a bullseye feature comprising a two-dimensional array of bullseyes, a triangle feature comprising at least one isosceles triangle, or a symmetric corners feature comprising two symmetric sets of geometric shapes arranged in an L-shape.
Control processes for a slide-scanning system comprising a carousel with a plurality of rack slots configured to receive slide racks via an exposed portion of the scanning system. In an embodiment, initializing the scanning system comprises automatically homing back-end and front-end components, wherein the front-end components comprise the carousel. An inventory of all slide racks in the carousel is automatically generated. If any slide rack was being processed by any back-end components, the slide rack is automatically unloaded into a corresponding rack slot. In addition, the carousel is automatically positioned to expose a starting subset of the rack slots within the exposed portion. This starting subset may comprise a maximum segment of adjacent empty rack slots.
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
G01N 35/02 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet en utilisant une série de récipients à échantillons déplacés par un transporteur passant devant un ou plusieurs postes de traitement ou d'analyse
85.
DIGITAL PATHOLOGY APPARATUS HOUSING WITH RAIL SYSTEM, SPEAKERLESS AUDIO SYSTEM, AND ELECTROMAGNETIC RADIATION SHIELDING
A digital pathology apparatus includes a housing with a rail system that allows the housing to slide off of the apparatus to expose the internal elements of the apparatus for easy maintenance. The housing includes a latch and sensor system that securely latches the housing in the closed position and senses when the housing is opened so that the moving parts of the apparatus can be safely stopped to avoid potential injury. The housing also includes electromagnetic shielding on a minimal portion of its interior surface to reduce electromagnetic radiation emanating from the apparatus. The digital pathology apparatus also includes a spearkerless audio system that engages with a portion of the interior surface of the housing that is not covered with electromagnetic shielding. The speakerless audio system provides an audio user interface while maintaining a contiguous surface on the housing to cover the digital pathology apparatus.
Graphical user interface for managing a workflow of a slide scanning system. In an embodiment, the graphical user interface comprises a graphical representation of a carousel used by the scanning system. The graphical representation of the carousel comprises a graphical representation of each of a plurality of rack slots, configured to receive slide racks. The graphical representation of the carousel indicates a position of the carousel, and the graphical representation of each of the plurality of rack slots indicates a status of the represented rack slot and/or a slide rack within the represented rack slot.
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G06F 3/0488 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] utilisant des caractéristiques spécifiques fournies par le périphérique d’entrée, p. ex. des fonctions commandées par la rotation d’une souris à deux capteurs, ou par la nature du périphérique d’entrée, p. ex. des gestes en fonction de la pression exercée enregistrée par une tablette numérique utilisant un écran tactile ou une tablette numérique, p. ex. entrée de commandes par des tracés gestuels
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
A stall detection system is provided that determines if a glass slide in motion during an automated process is at risk for being damaged and stops motion in the event of an unacceptable risk of damage. The system includes one or more motors configured to move a glass slide (directly or indirectly). The motors are configured to generate a load resistance value. The system includes one or more processors that monitor the load resistance value of a motor during motion and compares the load resistance value to a predetermined threshold resistance value to determine the risk of a glass slide being damaged. The predetermined threshold resistance value may correspond to a risk of slide breakage in response to a force applied to any surface of the slide, or a risk of losing a controlling grip on a slide rack, or a risk of a motor skipping a motor step.
A stuck slide determination system is provided that determines if a slide (e.g., glass slide), positioned on a scanning stage at the start of the scanning process, gets stuck and does not move along with the scanning stage after the scanning process commences. In an embodiment, the system includes a sensor having a transmitter and receiver that are relatively positioned to detect the presence of the stage or a slide or the absence of the stage or a slide. When the scanning stage begins to move at the start of the scanning process, a processor monitors a signal from the sensor and determines if the slide is improperly positioned after the scanning process has commenced. If the slide is improperly positioned, the processor stops movement of the scanning stage in order to protect the slide from damage.
B65G 43/00 - Dispositifs de commande, p. ex. de sécurité, d'alarme ou de correction des erreurs
G01V 8/12 - Détection, p. ex. en utilisant des barrières de lumière en utilisant un émetteur et un récepteur
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
Medical image based collaboration system and methods are provided. A collaboration server 40 creates a medical image based case in response to a request from a requesting system 10 and populates the case with the minimum required information comprising at least a digital medical image and a case number. The collaboration server 40 provides the medical image based case to a consulting system 30 and receives analysis information in response. The collaboration server 40 stores the analysis information in association with the medical image based case and provides the analysis information to the consulting system 30 to complete the medical image based collaboration.
G16H 30/20 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le maniement d’images médicales, p. ex. DICOM, HL7 ou PACS
G06Q 10/101 - Création collaborative, p. ex. développement conjoint de produits ou de services
G16H 80/00 - TIC spécialement adaptées pour faciliter la communication entre les professionnels de la santé ou les patients, p. ex. pour le diagnostic collaboratif, la thérapie collaborative ou la surveillance collaborative de l’état de santé
G16H 40/67 - TIC spécialement adaptées à la gestion ou à l’administration de ressources ou d’établissements de santéTIC spécialement adaptées à la gestion ou au fonctionnement d’équipement ou de dispositifs médicaux pour le fonctionnement d’équipement ou de dispositifs médicaux pour le fonctionnement à distance
G06Q 50/22 - Aide sociale ou assistance sociale, p. ex. activités de développement communautaire ou services de consultation
90.
NEURAL NETWORK BASED IDENTIFICATION OF AREAS OF INTEREST IN DIGITAL PATHOLOGY IMAGES
A CNN is applied to a histological image to identify areas of interest. The CNN classifies pixels according to relevance classes including one or more classes indicating levels of interest and at least one class indicating lack of interest. The CNN is trained on a training data set including data which has recorded how pathologists have interacted with visualizations of histological images. In the trained CNN, the interest-based pixel classification is used to generate a segmentation mask that defines areas of interest. The mask can be used to indicate where in an image clinically relevant features may be located. Further, it can be used to guide variable data compression of the histological image. Moreover, it can be used to control loading of image data in either a client-server model or within a memory cache policy. Furthermore, a histological image of a tissue sample of a tissue type that has been treated with a test compound is image processed in order to detect areas where toxic reactions to the test compound may have occurred. An autoencoder is trained with a training data set comprising histological images of tissue samples which are of the given tissue type, but which have not been treated with the test compound. The trained autoencoder is applied to detect tissue areas by their deviation from the normal variation seen in that tissue type as learnt by the training process, and so build up a toxicity map of the image. The toxicity map can then be used to direct a toxicological pathologist to examine the areas identified by the autoencoder as lying outside the normal range of heterogeneity for the tissue type. This makes the pathologist's review quicker and more reliable. The toxicity map can also be overlayed with the segmentation mask indicating areas of interest. When an area of interest and an area identified as lying outside the normal range of heterogeneity for the tissue type, and increased confidence score is applied to the overlapping area.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06K 9/46 - Extraction d'éléments ou de caractéristiques de l'image
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
91.
ARTIFICIAL INTELLIGENCE PROCESSING SYSTEM AND AUTOMATED PRE-DIAGNOSTIC WORKFLOW FOR DIGITAL PATHOLOGY
A digital pathology system comprising an AI processing module configured to invoke an instance of an AI processing application for processing image data from a histological image and an application module configured to invoke an instance of an application operable to perform an image processing task on a histological image associated with a patient record, wherein the image processing task includes an AI element. The application creates processing jobs to handle the AI elements of its task which are handled by the AI processing module. The AI processing module may be a CNN that processes a histological image to identify tumors by classifying image pixels into one of multiple tissue classes of tumorous or non-tumorous tissue. A test ordering module automatically determines based on identified tissue classes whether additional tests should be performed on the tissue sample. For each additional test, an order is automatically created and submitted. Advantageously, upon first review by a pathologist, the patient record includes the histological image and results from the automatically ordered additional tests.
G16H 30/20 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le maniement d’images médicales, p. ex. DICOM, HL7 ou PACS
G16H 30/40 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le traitement d’images médicales, p. ex. l’édition
G16H 50/20 - TIC spécialement adaptées au diagnostic médical, à la simulation médicale ou à l’extraction de données médicalesTIC spécialement adaptées à la détection, au suivi ou à la modélisation d’épidémies ou de pandémies pour le diagnostic assisté par ordinateur, p. ex. basé sur des systèmes experts médicaux
92.
COMPUTER SUPPORTED REVIEW OF TUMORS IN HISTOLOGY IMAGES AND POST OPERATIVE TUMOR MARGIN ASSESSMENT
A computer apparatus and method for identifying and visualizing tumors in a histological image and measuring a tumor margin are provided. A CNN is used to classify pixels in the image according to whether they are determined to relate to non-tumorous tissue, or one or more classes for tumorous tissue. Segmentation is carried out based on the CNN results to generate a mask that marks areas occupied by individual tumors. Summary statistics for each tumor are computed and supplied to a filter which edits the segmentation mask by filtering out tumors deemed to be insignificant. Optionally, the tumors that pass the filter may be ranked according to the summary statistics, for example in order of clinical relevance or by a sensible order of review for a pathologist. A visualization application can then display the histological image having regard to the segmentation mask, summary statistics and/or ranking. Tumor masses extracted by resection are painted with an ink to highlight its surface region. The CNN is trained to distinguish ink and no-ink tissue as well as tumor and no-tumor tissue. The CNN is applied to the histological image to generate an output image whose pixels are assigned to the tissue classes. Tumor margin status of the tissue section is determined by the presence or absence of tumor-and-ink classified pixels. Tumor margin involvement and tumor margin distance are determined by computing additional parameters based on classification-specified inter-pixel distance parameters.
Systems and methods for managing a plurality of scanning devices in a high-throughput laboratory environment. Each of the scanning devices is configured for a remote boot operation from an administrative server that is communicatively coupled with the plurality of scanning devices via a local network. The remote boot replaces the complete operational firmware of a scanning device. The scanning devices are each configured to periodically provide operational information to the administrative server for centralized storage. The centralized storage of operational information for each of the plurality of scanning devices, coupled with the ability of the administrative server to initiate a reboot of any scanning device and thereby update the complete operational firmware of the scanning device, allows for centralized administration of multiple scanning devices that facilitates configuration, support, image data storage, and/or communication with outside servers.
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
94.
Processing of histology images with a convolutional neural network to identify tumors
A convolutional neural network (CNN) is applied to identifying tumors in a histological image. The CNN has one channel assigned to each of a plurality of tissue classes that are to be identified, there being at least one class for each of non-tumorous and tumorous tissue types. Multi-stage convolution is performed on image patches extracted from the histological image followed by multi-stage transpose convolution to recover a layer matched in size to the input image patch. The output image patch thus has a one-to-one pixel-to-pixel correspondence with the input image patch such that each pixel in the output image patch has assigned to it one of the multiple available classes. The output image patches are then assembled into a probability map that can be co-rendered with the histological image either alongside it or over it as an overlay. The probability map can then be stored linked to the histological image.
G06K 9/00 - Méthodes ou dispositions pour la lecture ou la reconnaissance de caractères imprimés ou écrits ou pour la reconnaissance de formes, p.ex. d'empreintes digitales
G06N 5/04 - Modèles d’inférence ou de raisonnement
G16H 30/20 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le maniement d’images médicales, p. ex. DICOM, HL7 ou PACS
G06K 9/62 - Méthodes ou dispositions pour la reconnaissance utilisant des moyens électroniques
G06V 10/44 - Extraction de caractéristiques locales par analyse des parties du motif, p. ex. par détection d’arêtes, de contours, de boucles, d’angles, de barres ou d’intersectionsAnalyse de connectivité, p. ex. de composantes connectées
G06V 20/69 - Objets microscopiques, p. ex. cellules biologiques ou pièces cellulaires
A slide rack determination system for a digital slide scanning apparatus. In an embodiment, a motor drives a slide rack at a known rate toward an engagement surface. The elapsed time until engagement may be used to detect the presence or absence of the slide rack and/or the height of the slide rack. In addition, one or more sensors may detect one or more features of the slide rack, and these feature(s) may be used to determine the presence or absence of a slide rack, whether usage of the slide rack is supported or unsupported by the digital slide scanning apparatus, the orientation of the slide rack, and/or the manufacturer and/or model of the slide rack.
H04N 1/00 - Balayage, transmission ou reproduction de documents ou similaires, p. ex. transmission de fac-similésLeurs détails
H04N 1/12 - Dispositions de balayage utilisant l'avance de la feuille comme composant de balayage lente
H04N 3/02 - Détails des dispositifs de balayage des systèmes de télévisionLeur combinaison avec la production des tensions d'alimentation par des moyens optiques-mécaniques uniquement
96.
Systems and methods for an image repository for pathology
Systems and methods for managing an image repository for pathology. In an embodiment, a search request is received. One or more digital slide images are identified from an image repository based on the search request. A user is provided access to the identified digital slide images. In addition, each of a plurality of collections of digital slide images are associated with a search rating, and a value for each of the plurality of collections is computed based on the associated search rating and a size of the collection.
G06F 16/58 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
G06Q 30/06 - Transactions d’achat, de vente ou de crédit-bail
G16H 30/20 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le maniement d’images médicales, p. ex. DICOM, HL7 ou PACS
G16H 30/40 - TIC spécialement adaptées au maniement ou au traitement d’images médicales pour le traitement d’images médicales, p. ex. l’édition
G16H 70/00 - TIC spécialement adaptées au maniement ou au traitement de références médicales
G06Q 20/14 - Architectures de paiement spécialement adaptées aux systèmes de facturation
G16Z 99/00 - Matière non prévue dans les autres groupes principaux de la présente sous-classe
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Image and data (case) management software for the uploading
and management of pathology data; software for use in the
medical imaging field, namely, pathology, microscopy,
histology, cytology, radiology, and hematology; software for
enabling remote or local storing, viewing, annotating,
analysis and registration of digital images and performing
digital image management in the fields of pathology,
microscopy, histology, cytology, radiology, and hematology;
image management software for creating, storing and managing
a hierarchy of medical cases, with each case comprising
digital slides, metadata, a case history, analysis results,
and a specimen description; case management software for
use, collaboration and consultation in the fields of
pathology, microscopy, histology, cytology, radiology, and
hematology; software for storing, viewing and annotating
digital slides, consolidating case information, test
results, diagnosis information, comments, and digital images
into a case report; laboratory information management and
workflow software; software for quality control/quality
assurance in the fields of pathology, digital pathology,
microscopy, cytology, histology, cytology, radiology, and
hematology; software for image analysis and registration. Software as a service (saas) services featuring software for
providing a remotely accessible image management and viewing
system and educational materials for medical personnel;
providing web-based, non-downloadable software for use in
the medical imaging field, namely, pathology, microscopy,
histology, cytology, radiology, and hematology; providing
web-based, non-downloadable software for enabling remote or
local storing, viewing, annotating, analysis and
registration of digital images and performing digital image
management in the fields of pathology, microscopy,
histology, cytology, radiology, and hematology; providing
web-based, non-downloadable image management software for
creating and managing a hierarchy of medical cases, with
each case comprising digital slides, metadata, a case
history, analysis results, and a specimen description;
providing web-based, non-downloadable case management
software for use in the fields of pathology, microscopy,
histology, cytology, radiology, and hematology; providing
web-based, non-downloadable software for viewing and
annotating digital slides, consolidating case information,
test results, diagnosis information, comments, and digital
images into a case report, and generating, exporting, and
printing case reports for providing audit trails in the
medical imaging field; providing web-based, non-downloadable
laboratory information management and workflow software;
providing web-based, non-downloadable software for quality
control and quality assurance in the fields of pathology,
digital pathology, microscopy, cytology, histology,
cytology, radiology, and hematology; providing web-based,
non-downloadable software for software for image analysis
and registration; consulting and technical assistance with
computer-based information systems and components, namely,
in the field of medical imaging including the storage and
management of medical images and digital pathology;
technological consulting and assistance with laboratory
workflow, quality control and quality assurance, image
processing, and image workflow in the areas of digital
pathology and medical imaging; virtual microscopy services,
namely, converting glass microscope slides to high
resolution digital images of slides that can be viewed,
integrated with other associated data, managed and analyzed;
providing internet based data storage and recovery services
for digitized images, in the fields of virtual microscopy,
digital pathology, digital cytology, digital hematology and
medical information technology.
A slide rack clamp apparatus that secures a slide rack in a digital slide scanning apparatus. In an embodiment, the slide rack clamp apparatus includes an upper clamp and a lower clamp. Each clamp comprises one or more clamp projections, which are configured to engage one or more recesses in engagement surfaces of a plurality of different slide racks from different manufacturers. The lower clamp is driven by a motor along a linear axis to engage the lower clamp projections with the one or more slide rack recesses of the bottom surface of the slide rack. The motor drives the lower clamp and the engaged slide rack upward to engage the one or more slide rack recesses of the top surface of the slide rack with the clamp projections of the upper clamp to fully engage the slide rack between the upper clamp and the lower clamp.
G01N 35/10 - Dispositifs pour transférer les échantillons vers, dans ou à partir de l'appareil d'analyse, p. ex. dispositifs d'aspiration, dispositifs d'injection
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
A power off delay system and method is configured to delay termination of electrical power to a digital pathology device in a power off condition. If the apparatus includes a UPS, the power off delay system and method delays termination of electrical power when a power switch is turned off and when a catastrophic power failure occurs. During the delay of the termination of electrical power, the digital pathology device is configured to control the scanning stage system and the glass slide conveyor system and the slide rack conveyor system to place each of these systems into a known state and position all glass slides into a known position prior to the termination of electrical power to the digital pathology device. This allows the digital pathology device to resume normal operation upon power up.
G01N 35/00 - Analyse automatique non limitée à des procédés ou à des matériaux spécifiés dans un seul des groupes Manipulation de matériaux à cet effet
G02B 21/26 - PlatinesMoyens de réglage pour celles-ci
G02B 21/34 - Lames de microscope, p. ex. montage d'échantillons sur des lames de microscope
H02J 9/06 - Circuits pour alimentation de puissance de secours ou de réserve, p. ex. pour éclairage de secours dans lesquels le système de distribution est déconnecté de la source normale et connecté à une source de réserve avec commutation automatique
