Abstract: The present invention relates to computer implemented methods and systems for processing medical image. The methods include receiving (101) a first acquired image of a patient, wherein the first acquired image is a medical image acquired using a medical imaging device. The first acquired image is compared (102) to a plurality of reference images by determining a first plurality of confidence metrics using a first calculation method. The first plurality of confidence metrics for the first acquired image are output (103). Each respective confidence metric of the first plurality of confidence metrics indicates how closely the first acquired image matches a respective reference image of the plurality of reference images.

Abstract: A method is provided for adapting a 3D field of view (FOV) in ultrasound data acquisition so as to minimize the FOV volume in a manner that is controlled and precise. The method comprises defining a volumetric region across which 3D ultrasound data is desired, and then adapting the data acquisition field of view (FOV) in dependence upon the defined volumetric region, to encompass the region. This is achieved based on adapting a scan line length (or scan depth) of each individual scan line based on the defined volumetric region. In some embodiments, the volumetric region may be defined based on anatomical segmentation of a reference ultrasound dataset acquired in an initial step, and setting the volumetric region in dependence upon boundaries of an identified object of interest. The volumetric region may in a subset of embodiments be set as the region occupied by a detected anatomical object of interest.

Abstract: A method (100) for providing an analysis of coronary artery disease (CAD), comprising: (i) receiving (120) patient metadata about the patient; (ii) receiving (130) a temporal sequence of 2D and/or 3D ultrasound images of the patient's heart; (iii) selecting (140), by the CAD prediction system, a plurality of ultrasound images from the temporal sequence; (iv) processing (150), using a trained AI algorithm of the CAD prediction system, the selected plurality of ultrasound images to generate a feature map of the selected plurality of ultrasound images; (v) analyzing (160) the generated feature map and the received patient metadata using a trained algorithm of the CAD prediction system to generate a CAD prediction output; (vi) providing (170), via a user interface of the CAD prediction system, the generated CAD prediction output.

Abstract: A system and method for providing an enhancing or contrast agent advisability indicator. Subject data for a subject is processed using an AI-based model to obtain an indication of whether a medical imaging procedure for the subject requires an enhancing or contrast agent. The enhancing or contrast agent advisability indicator is generated with respect to one or more target pathologies assessed in the medical imaging procedure.

Abstract: A computer implemented method for collating patient data for analysis comprises receiving a set of input data comprising a plurality of patient data records, wherein the plural patient data records comprise medical imaging data and at least one other patient data type; and generating a vector for each of the plural patient data records by processing each patient data record using a corresponding encoding algorithm, wherein the encoding algorithm used to generate the vector is selected based on the type of patient data record and wherein the vectors are for use by a machine learning model.

Abstract: A method is provided for adapting a 3D field of view (FOV) in ultrasound data acquisition so as to minimize the FOV volume in a manner that is controlled and precise. The method comprises defining a volumetric region across which 3D ultrasound data is desired, and then adapting the data acquisition field of view (FOV) in dependence upon the defined volumetric region, to encompass the region. This is achieved based on adapting a scan line length (or scan depth) of each individual scan line based on the defined volumetric region. In some embodiments, the volumetric region may be defined based on anatomical segmentation of a reference ultrasound dataset acquired in an initial step, and setting the volumetric region in dependence upon boundaries of an identified object of interest. The volumetric region may in a subset of embodiments be set as the region occupied by a detected anatomical object of interest.

Abstract: An ultrasound imaging system performs real-time image analysis of the 3D ultrasound images to identify anatomical structure and landmarks in the 3D images, so that it can be determined if a region of interest of a target anatomical structure is present. If the region of interest is not present, the location of the region of interest outside the field of view volume is inferred from the anatomical structure and landmarks that are detected within the field of view. A relative displacement between the reference anatomical plane and a position and orientation of the 3D ultrasound imaging probe can then be derived so that ultrasound guidance information can be given.

Abstract: The present disclosure relates to a system for patient-specific intervention planning, the system comprising a physical model of an anatomical structure, wherein the physical model is a patient-specific model based on medical image data; a virtual model of the anatomical structure, wherein the virtual model is a patient-specific model based on medical image data; a tracking device configured to track a position of a physical representation of an interventional tool with respect to the physical model of the anatomical structure; a processor configured to perform the step of: registering the physical model of the anatomical structure with the virtual model of the anatomical structure and registering the physical representation of the interventional tool with a virtual representation of the interventional tool based on the position of the physical representation of the interventional tool and the physical model of the anatomical structure.

Abstract: The invention provides a method for generating a transvalvular pressure quantification within a cavity. The method includes acquiring a plurality of color Doppler ultrasound image frames, wherein the image frames comprise a view of a valve, one of which is then presented to a user. The user may then provide an input to indicate the location of the valve within the image frame. The location of the valve is then tracked within the remaining image frames based on the user input. A vector flow is estimated based on the color Doppler image frames and the tracked location of the valve, which may be used to estimate the flow across the valve(s) and in the cavity.

Abstract: The present disclosure relates to a system for patient-specific intervention planning, the system comprising a physical model of an anatomical structure, wherein the physical model is a patient-specific model based on medical image data; a virtual model of the anatomical structure, wherein the virtual model is a patient-specific model based on medical image data; a tracking device configured to track a position of a physical representation of an interventional tool with respect to the physical model of the anatomical structure; a processor configured to perform the step of: registering the physical model of the anatomical structure with the virtual model of the anatomical structure and registering the physical representation of the interventional tool with a virtual representation of the interventional tool based on the position of the physical representation of the interventional tool and the physical model of the anatomical structure.