Unsupervised Mitral Valve Segmentation in Echocardiography with Neural Network Matrix Factorization
Mitral valve segmentation specifies a crucial first step to establish a machine learning pipeline that can support practitioners into performing diagnosis of mitral valve diseases, surgical planning, and intraoperative procedures. To this end, we propose a totally automated and unsupervised mitral valve segmentation algorithm, based on a low dimensional neural network matrix factorization of echocardiography videos. The method is evaluated in a collection of echocardiography videos of patients with a variety of mitral valve diseases and exceeds the state of the art method in all the metrics considered.
AIME