Abstract: The diagnostic vector classification support system and method disclosed herein may both reduce the time and effort required to train radiologists to interpret medical images, and provide a decision support system for trained radiologists who, regardless of training, have the potential to miss relevant findings. In an embodiment, a morphological image is used to identify a zone of interest in a co-registered functional image. An operator's grading of a feature at least partially contained within the zone of interest is compared to one or more computer-generated grades for the feature. Where the operator and computer-generated grades differ, diagnostic support can be provided such as displaying additional images, revising the zone of interest, annotating one or more displayed images, displaying a computer-generated feature grade, among other possibilities disclosed herein.

Abstract: The diagnostic vector classification support system and method disclosed herein may both reduce the time and effort required to train radiologists to interpret medical images, and provide a decision support system for trained radiologists who, regardless of training, have the potential to miss relevant findings. In an embodiment, a morphological image is used to identify a zone of interest in a co-registered functional image. An operator's grading of a feature at least partially contained within the zone of interest is compared to one or more computer-generated grades for the feature. Where the operator and computer-generated grades differ, diagnostic support can be provided such as displaying additional images, revising the zone of interest, annotating one or more displayed images, displaying a computer-generated feature grade, among other possibilities disclosed herein.

Abstract: Systems, methods and computer program products are provided for reading and scoring ultrasound and/or optoacoustic (US/OA) images that include at least one of OA images or US images acquired in connection with an examination for a region of interest (ROI). The system displays a first image that has an interior ROI outline separating an internal zone from a boundary zone. In some aspects, feature scores are obtained in connection with at least the boundary zone and peripheral zone of the first image and the feature scores are applied to a classification model to obtain at least one of a prognostic result or predictive result indicative of a trait of the lesion. In accordance with some aspects, an order in which feature scores are entered is automatically managed to obtain for the at least one of the peripheral zone or the boundary zone before the feature score is obtained for the internal zone.

Abstract: Systems, methods and computer program products are provided for analyzing at least one of ultrasound (US) images or optoacoustic (OA) images (US/OA images), comprising: a display configured to display at least a first image from at least one of OA images or US images acquired in connection with an examination for a region of interest (ROI), the first image including a lesion, the first image overlaid with an interior ROI outline separating an internal zone from a boundary zone of the ROI, the first image overlaid with an exterior ROI outline separating the boundary zone from a peripheral zone; a graphical user interface (GUI); memory configured to store program instructions; and one or more processors configured to execute the programmable instructions to: obtain feature scores in connection with at least the boundary zone and peripheral zone of the first image; apply the feature scores to a classification model to obtain predictive result indicative of a trait of the lesion, the predictive result indicating

Abstract: Systems, methods and computer program products are provided for reading and scoring ultrasound and/or optoacoustic (US/OA) images that include at least one of OA images or US images acquired in connection with an examination for a region of interest (ROI). The system displays a first image that has an interior ROI outline separating an internal zone from a boundary zone. In some aspects, feature scores are obtained in connection with at least the boundary zone and peripheral zone of the first image and the feature scores are applied to a classification model to obtain at least one of a prognostic result or predictive result indicative of a trait of the lesion. In accordance with some aspects, an order in which feature scores are entered is automatically managed to obtain for the at least one of the peripheral zone or the boundary zone before the feature score is obtained for the internal zone.

Abstract: Methods, devices and systems are provided that utilize one or more processors in connection with, receiving OA/US feature scores in connection with OA/US images collected from a patient examination for a volume of interest. The methods, devices and systems apply the OA/US feature scores to a feature score to molecular subtype (FSMS) model. The methods, devices and systems determine, from the FSMS model, an indication of at least one of a molecular subtype or histologic grade of a pathology experienced by the patient.

Abstract: Methods, devices and systems are provided that utilize one or more processors in connection with, receiving OA/US feature scores in connection with OA/US images collected from a patient examination for a volume of interest. The methods, devices and systems apply the OA/US feature scores to a feature score to molecular subtype (FSMS) model. The methods, devices and systems determine, from the FSMS model, an indication of at least one of a molecular subtype or histologic grade of a pathology experienced by the patient.

Abstract: The diagnostic vector classification support system and method disclosed herein may both reduce the time and effort required to train radiologists to interpret medical images, and provide a decision support system for trained radiologists who, regardless of training, have the potential to miss relevant findings. In an embodiment, a morphological image is used to identify a zone of interest in a co-registered functional image. An operator's grading of a feature at least partially contained within the zone of interest is compared to one or more computer-generated grades for the feature. Where the operator and computer-generated grades differ, diagnostic support can be provided such as displaying additional images, revising the zone of interest, annotating one or more displayed images, displaying a computer-generated feature grade, among other possibilities disclosed herein.

Abstract: The diagnostic vector classification support system and method disclosed herein may both reduce the time and effort required to train radiologists to interpret medical images, and provide a decision support system for trained radiologists who, regardless of training, have the potential to miss relevant findings. In an embodiment, a morphological image is used to identify a zone of interest in a co-registered functional image. An operator's grading of a feature at least partially contained within the zone of interest is compared to one or more computer-generated grades for the feature. Where the operator and computer-generated grades differ, diagnostic support can be provided such as displaying additional images, revising the zone of interest, annotating one or more displayed images, displaying a computer-generated feature grade, among other possibilities disclosed herein.

Abstract: Systems, methods and computer program products are provided for reading and scoring ultrasound and/or optoacoustic (US/OA) images that include at least one of OA images or US images acquired in connection with an examination for a region of interest (ROI). The system displays a first image that has an interior ROI outline separating an internal zone from a boundary zone. In some aspects, feature scores are obtained in connection with at least the boundary zone and peripheral zone of the first image and the feature scores are applied to a classification model to obtain at least one of a prognostic result or predictive result indicative of a trait of the lesion. In accordance with some aspects, an order in which feature scores are entered is automatically managed to obtain for the at least one of the peripheral zone or the boundary zone before the feature score is obtained for the internal zone.

Abstract: Systems, methods and computer program products are provided for reading and scoring ultrasound and/or optoacoustic (US/OA) images that include at least one of OA images or US images acquired in connection with an examination for a region of interest (ROI). The system displays a first image that has an interior ROI outline separating an internal zone from a boundary zone. In some aspects, feature scores are obtained in connection with at least the boundary zone and peripheral zone of the first image and the feature scores are applied to a classification model to obtain at least one of a prognostic result or predictive result indicative of a trait of the lesion. In accordance with some aspects, an order in which feature scores are entered is automatically managed to obtain for the at least one of the peripheral zone or the boundary zone before the feature score is obtained for the internal zone.

Abstract: Methods, devices and systems are provided that utilize one or more processors in connection with, receiving OA/US feature scores in connection with OA/US images collected from a patient examination for a volume of interest. The methods, devices and systems apply the OA/US feature scores to a feature score to molecular subtype (FSMS) model. The methods, devices and systems determine, from the FSMS model, an indication of at least one of a molecular subtype or histologic grade of a pathology experienced by the patient.

Abstract: In an embodiment, an apparatus for opto-acoustic imaging includes a first contact area adapted to apply a first pressure to a surface of an imaging volume of a subject and a second contact area adapted to apply a second pressure to the surface. The second contact area is configured to provide decreased blood exit from the imaging volume by restricting flow relative to the first contact area. An optical energy output port is provided to illuminate the imaging volume to produce opto-acoustic signals from an absorbed optical energy of blood in the imaging volume. The opto-acoustic signals are detected by one or more ultrasound transducers and processed by a processor to generate images of the volume. An image generated by processing the detected opto-acoustic signals is output on a display.

Abstract: The diagnostic vector classification support system and method disclosed herein may both reduce the time and effort required to train radiologists to interpret medical images, and provide a decision support system for trained radiologists who, regardless of training, have the potential to miss relevant findings. In an embodiment, a morphological image is used to identify a zone of interest in a co-registered functional image. An operator's grading of a feature at least partially contained within the zone of interest is compared to one or more computer-generated grades for the feature. Where the operator and computer-generated grades differ, diagnostic support can be provided such as displaying additional images, revising the zone of interest, annotating one or more displayed images, displaying a computer-generated feature grade, among other possibilities disclosed herein.

Abstract: The diagnostic vector classification support system and method disclosed herein may both reduce the time and effort required to train radiologists to interpret medical images, and provide a decision support system for trained radiologists who, regardless of training, have the potential to miss relevant findings. In an embodiment, a morphological image is used to identify a zone of interest in a co-registered functional image. An operator's grading of a feature at least partially contained within the zone of interest is compared to one or more computer-generated grades for the feature. Where the operator and computer-generated grades differ, diagnostic support can be provided such as displaying additional images, revising the zone of interest, annotating one or more displayed images, displaying a computer-generated feature grade, among other possibilities disclosed herein.

Abstract: The diagnostic vector classification support system and method disclosed herein may both reduce the time and effort required to train radiologists to interpret medical images, and provide a decision support system for trained radiologists who, regardless of training, have the potential to miss relevant findings. In an embodiment, a morphological image is used to identify a zone of interest in a co-registered functional image. An operator's grading of a feature at least partially contained within the zone of interest is compared to one or more computer-generated grades for the feature. Where the operator and computer-generated grades differ, diagnostic support can be provided such as displaying additional images, revising the zone of interest, annotating one or more displayed images, displaying a computer-generated feature grade, among other possibilities disclosed herein.

Abstract: The diagnostic vector classification support system and method disclosed herein may both reduce the time and effort required to train radiologists to interpret medical images, and provide a decision support system for trained radiologists who, regardless of training, have the potential to miss relevant findings. In an embodiment, a morphological image is used to identify a zone of interest in a co-registered functional image. An operator's grading of a feature at least partially contained within the zone of interest is compared to one or more computer-generated grades for the feature. Where the operator and computer-generated grades differ, diagnostic support can be provided such as displaying additional images, revising the zone of interest, annotating one or more displayed images, displaying a computer-generated feature grade, among other possibilities disclosed herein.

Abstract: In an embodiment, an apparatus for opto-acoustic imaging includes a first contact area adapted to apply a first pressure to a surface of an imaging volume of a subject and a second contact area adapted to apply a second pressure to the surface. The second contact area is configured to provide decreased blood exit from the imaging volume by restricting flow relative to the first contact area. An optical energy output port is provided to illuminate the imaging volume to produce opto-acoustic signals from an absorbed optical energy of blood in the imaging volume. The opto-acoustic signals are detected by one or more ultrasound transducers and processed by a processor to generate images of the volume. An image generated by processing the detected opto-acoustic signals is output on a display.

Abstract: The diagnostic vector classification support system and method disclosed herein may both reduce the time and effort required to train radiologists to interpret medical images, and provide a decision support system for trained radiologists who, regardless of training, have the potential to miss relevant findings. In an embodiment, a morphological image is used to identify a zone of interest in a co-registered functional image. An operator's grading of a feature at least partially contained within the zone of interest is compared to one or more computer-generated grades for the feature. Where the operator and computer-generated grades differ, diagnostic support can be provided such as displaying additional images, revising the zone of interest, annotating one or more displayed images, displaying a computer-generated feature grade, among other possibilities disclosed herein.