Abstract: There is provided a method of processing 2D ultrasound images for computing clinical parameter(s) of a right ventricle (RV), comprising: selecting one 2D ultrasound image of 2D ultrasound images depicting the RV, interpolating an inner contour of an endocardial border of the RV for the selected 2D image, tracking the interpolated inner contour obtained for the one 2D ultrasound image over the 2D images over cardiac cycle(s), computing a RV area of the RV for each respective 2D image according to the tracked interpolated inner contour, identifying a first 2D image depicting an end-diastole (ED) state according to a maximal value of the RV area for the 2D images, and a second 2D US image depicting an end-systole (ES) state according to minimal value of the RV area for the 2D images, and computing clinical parameter(s) of the RV according to the identified first and second 2D images.

Abstract: There is provided a method of processing 2D ultrasound images for computing clinical parameter(s) of a right ventricle (RV), comprising: selecting one 2D ultrasound image of 2D ultrasound images depicting the RV, interpolating an inner contour of an endocardial border of the RV for the selected 2D image, tracking the interpolated inner contour obtained for the one 2D ultrasound image over the 2D images over cardiac cycle(s), computing a RV area of the RV for each respective 2D image according to the tracked interpolated inner contour, identifying a first 2D image depicting an end-diastole (ED) state according to a maximal value of the RV area for the 2D images, and a second 2D US image depicting an end-systole (ES) state according to minimal value of the RV area for the 2D images, and computing clinical parameter(s) of the RV according to the identified first and second 2D images.

Abstract: There is provided a method of processing 2D ultrasound images for computing clinical parameter(s) of a right ventricle (RV), comprising: selecting one 2D ultrasound image of 2D ultrasound images depicting the RV, interpolating an inner contour of an endocardial border of the RV for the selected 2D image, tracking the interpolated inner contour obtained for the one 2D ultrasound image over the 2D images over cardiac cycle(s), computing a RV area of the RV for each respective 2D image according to the tracked interpolated inner contour, identifying a first 2D image depicting an end-diastole (ED) state according to a maximal value of the RV area for the 2D images, and a second 2D US image depicting an end-systole (ES) state according to minimal value of the RV area for the 2D images, and computing clinical parameter(s) of the RV according to the identified first and second 2D images.

Abstract: A method for automatic left ventricular (LV) inner border detection, the method comprising: performing image mapping on an echocardiogram, to produce a multi-level image map; converting the image map into a binary image, by attributing pixels of one or more darker levels of the image map to the LV cavity and pixels of one or more lighter levels of the image map to the myocardium; applying a radial filter to contours of the myocardium in the binary image, to extract an approximate inner border of the LV; and performing shape modeling on the approximate inner border, to determine the LV inner border.