Abstract: Methods and systems for simulating a stent in a coronary artery lumen structure are disclosed. A method of simulating a stent in a coronary artery lumen structure, the method comprises: reconstructing a three-dimensional coronary artery tree from segmented coronary lumen contours; replacing part of the three-dimensional artery tree with a candidate stent structure; and simulating pressure distribution through the coronary artery tree to determine a non-invasive fractional flow reserve through the candidate stent structure.

Abstract: Embodiments include a patch-type, ultrasound sensor system and method to monitor the function and motion of a patients anatomical structure, comprising processing at least one received ultrasound image using one or more analytical tools, including radon transformation, higher-order spectra techniques, and/or active contour models, to generate at least one processed ultrasound image; inputting the at least one processed ultrasound image into a deep learning Convolutional Neural Network to obtain an automatic classification result selected from two or more classes indicating the functional state of the anatomical structure. The patch-type, ultrasound sensor system can communicate via a wireless or wired connection. The monitoring can be at rest or during surgery or other procedure or whilst the subject is exposed to any physiological stressors as part of medical examinations, and can be adapted for use in monitoring the function of body structures including the heart, blood vessels, lungs or joints.

Abstract: There is provided a method for geometrical reconstruction of an internal anatomical structure using at least one processor based on a set of contours derived from the internal anatomical structure, the set of contours including a first subset of long-axis contours obtained based on a first set of long-axis images of the internal anatomical structure. The method includes: adjusting the set of contours, comprising adjusting the first subset of long-axis contours to correct for motion artefacts in the first set of long-axis images; and deforming a template three-dimensional (3D) surface mesh preconfigured for the internal anatomical structure's type into a deformed 3D surface mesh based on the adjusted set of contours to obtain the geometrical reconstruction of the internal anatomical structure. In particular, the internal anatomical structure is a heart. There is also provided a corresponding system for geometrical reconstruction of an internal anatomical structure.

Abstract: The present disclosure generally relates to an automated method and system for generating a panoramic visualization of a coronary arterial tree of a subject. The method comprises: acquiring an image volume of a thoracic cavity of the subject, the image volume providing a three-dimensional (3D) representation of the thoracic cavity; isolating a coronary structure in the 3D representation by abating one or more other anatomical structures in the thoracic cavity; abating one or more portions of the coronary structure in the 3D representation that attenuate visualization of the coronary arterial tree; generating, by maximum intensity projection (MIP), a plurality of MIP images of the coronary structure from the 3D representation; and compositing the MIP images to generate the panoramic visualization of the coronary arterial tree.

Abstract: There is provided a method for geometrical reconstruction of an internal anatomical structure using at least one processor based on a set of contours derived from the internal anatomical structure, the set of contours including a first subset of long-axis contours obtained based on a first set of long-axis images of the internal anatomical structure. The method includes: adjusting the set of contours, comprising adjusting the first subset of long-axis contours to correct for motion artefacts in the first set of long-axis images; and deforming a template three-dimensional (3D) surface mesh preconfigured for the internal anatomical structure's type into a deformed 3D surface mesh based on the adjusted set of contours to obtain the geometrical reconstruction of the internal anatomical structure. In particular, the internal anatomical structure is a heart. There is also provided a corresponding system for geometrical reconstruction of an internal anatomical structure.

Abstract: A medical image processing method of determining a fractional flow reserve through a stenosis of a coronary artery from medical image data is disclosed. The medical image data comprises a set of images of a coronary region of a patient. The coronary region includes the stenosis. The method comprises: reconstructing a three dimensional model of a coronary artery tree of the patient from the medical image data; determining stenosis dimensions from the three dimensional model of the coronary artery tree of the patient; simulating blood flow in the three dimensional model of the coronary artery tree of the patient to determine modeled flow rates; using an analytical model depending on the stenosis dimensions to predict a modeled pressure drop over the stenosis from the modeled flow rates; and determining the fractional flow reserve through the stenosis from the modeled pressure drop.

Abstract: A method for assessing blood vessel stenosis using image data of a subject is disclosed. The image data represents a vascular structure of the subject. The method comprises: (a) segmenting, from the image data, a vessel segment representing a segment of a blood vessel, (b) obtaining, using the image data, a plurality of two-dimensional images of the vessel segment; said plurality of two-dimensional images representing respective cross-sections of the vessel segment, (c) identifying, for each of the plurality of two-dimensional images, a lumen area comprising lumen pixels representing a lumen of the corresponding cross-section, (d) obtaining a quantitative measure using the lumen areas of successive cross-sections of the vessel segment, and (e) assessing blood vessel stenosis using the quantitative measure. A computer system for performing the above method is disclosed.

Abstract: The present disclosure generally relates to an automated method and system for generating a panoramic visualization of a coronary arterial tree of a subject. The method comprises: acquiring an image volume of a thoracic cavity of the subject, the image volume providing a three-dimensional (3D) representation of the thoracic cavity; isolating a coronary structure in the 3D representation by abating one or more other anatomical structures in the thoracic cavity; abating one or more portions of the coronary structure in the 3D representation that attenuate visualization of the coronary arterial tree; generating, by maximum intensity projection (MIP), a plurality of MIP images of the coronary structure from the 3D representation; and compositing the MIP images to generate the panoramic visualization of the coronary arterial tree.

Abstract: A method is proposed for identifying an anatomical structure within a spatial-temporal image (i.e. a series of frames captured as respective times). A current frame of spatial-temporal medical image is processed using information from one or more previous and/or subsequent temporal frames, to aid in the segmentation of an object or a region of interest (ROI) in a current frame. The invention is applicable to both two- and three-dimensional spatial-temporal images (i.e., 2D+time or 3D+time), and in particular to cardiac magnetic resonance (CMR images). An initialization process for this method segments the left ventricle (LV) in a CMR image by a fuzzy c-means (FCM) clustering algorithm which employs a circular shape function as part of the definition of the dissimilarity measure.

Abstract: A method for assessing blood vessel stenosis using image data of a subject is disclosed. The image data represents a vascular structure of the subject. The method comprises: (a) segmenting, from the image data, a vessel segment representing a segment of a blood vessel, (b) obtaining, using the image data, a plurality of two-dimensional images of the vessel segment; said plurality of two-dimensional images representing respective cross-sections of the vessel segment, (c) identifying, for each of the plurality of two-dimensional images, a lumen area comprising lumen pixels representing a lumen of the corresponding cross-section, (d) obtaining a quantitative measure using the lumen areas of successive cross-sections of the vessel segment, and (e) assessing blood vessel stenosis using the quantitative measure. A computer system for performing the above method is disclosed.

Abstract: A medical image processing method of determining a fractional flow reserve through a stenosis of a coronary artery from medical image data is disclosed. The medical image data comprises a set of images of a coronary region of a patient. The coronary region includes the stenosis. The method comprises: reconstructing a three dimensional model of a coronary artery tree of the patient from the medical image data; determining stenosis dimensions from the three dimensional model of the coronary artery tree of the patient; simulating blood flow in the three dimensional model of the coronary artery tree of the patient to determine modeled flow rates; using an analytical model depending on the stenosis dimensions to predict a modeled pressure drop over the stenosis from the modeled flow rates; and determining the fractional flow reserve through the stenosis from the modeled pressure drop.

Abstract: A method is proposed for identifying an anatomical structure within a spatial-temporal image (i.e. a series of frames captured as respective times). A current frame of spatial-temporal medical image is processed using information from one or more previous and/or subsequent temporal frames, to aid in the segmentation of an object or a region of interest (ROI) in a current frame. The invention is applicable to both two- and three-dimensional spatial-temporal images (i.e., 2D+time or 3D+time), and in particular to cardiac magnetic resonance (CMR images). An initialisation process for this method segments the left ventricle (LV) in a CMR image by a fuzzy c-means (FCM) clustering algorithm which employs a circular shape function as part of the definition of the dissimilarity measure.

Abstract: A method and system are proposed to obtain quantitative data about the shape of a biological structure, and especially a heart ventricle. A set of three-dimensional input meshes are generated from MRI data. They represent the shape of a ventricle at successive times. The input meshes are used to generate a set of three-dimensional morphed meshes which have the same number of vertices as each other, and have respective shapes which are the shapes of corresponding ones of the input meshes. Then, for each of the times, shape analysis is performed to obtain a curvedness value at each of a plurality of corresponding locations in the morphed meshes. The curvedness value may be used to obtain a curvedness rate at each of the locations, indicative of the rate of change of curvedness with time at each of the locations.

Abstract: A method and system are proposed to obtain quantitative data about the shape of a biological structure, and especially a heart ventricle. A set of three-dimensional input meshes are generated from MRI data. They represent the shape of a ventricle at successive times. The input meshes are used to generate a set of three-dimensional morphed meshes which have the same number of vertices as each other, and have respective shapes which are the shapes of corresponding ones of the input meshes. Then, for each of the times, shape analysis is performed to obtain a curvedness value at each of a plurality of corresponding locations in the morphed meshes. The curvedness value may be used to obtain a curvedness rate at each of the locations, indicative of the rate of change of curvedness with time at each of the locations.