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.
CITATION STYLE
Corinzia, L., Provost, J., Candreva, A., Tamarasso, M., Maisano, F., & Buhmann, J. M. (2019). Unsupervised mitral valve segmentation in echocardiography with neural network matrix factorization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11526 LNAI, pp. 410–419). Springer Verlag. https://doi.org/10.1007/978-3-030-21642-9_51
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