A method for processing echocardiography data in order to enable automatic functional measurements based on cardiac ultrasound images as an input, the method comprising: (i) classification of the cardiac ultrasound images in order to ensure that relevant images are passed on to the next steps, optionally utilising a first neural network, or first part of a neural network, such as a convolutional neural network; (ii) segmentation and semantic partitioning of the left ventricle (LV) myocardium to extract relevant parts of the image, optionally by using a second neural network, or second part of a neural network; (iii) regional motion estimates to determine a mapping of displacements in the extracted parts of the imageand to output estimated tissue motion vectors for the extracted parts of the image, optionally using a third neural network, or third part of a neural network; and (iv) fusion of measurements via state estimation applied to the tissue motion vectors and thereby incorporating a temporal domain to produce data showing variation of the estimated measurements over time; wherein at least one of steps (i), (ii), and (iii) uses a neural network or a part of a neural network.
FUNCTIONAL MEASUREMENTS IN ECHOCARDIOGRAPHY