Abstract: A method for training a machine learning system, including: based on at least one image dataset representing at least one portion of the hollow structure, calculating a signed distance field of each portion and calculating at least one geometrical parameter of each portion; generating a deployed in-use representation of the device by computing contact forces between the device and each portion based on the signed distance field and by applying these contact forces to a geometrical representation of the device; and training the machine learning system with each calculated geometrical parameter as an input and the corresponding deployed in-use representation as an associated target output, the obtained trained machine learning system being configured to receive as input at least one geometrical parameter and provide as output the deployed in-use representation of the device.

Abstract: A computer-implemented method, a computer program, a storage medium, and a system for reconstructing a geometry of the mitral valve of a subject as open and as closed, based on a sequence of echography images acquired from the subject. The sequence of echography images represents the mitral valve apparatus during at least one heart cycle.