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Unsupervised Mitral Valve Segmentation in Echocardiography with Neural Network Matrix Factorization

  • Luca CorinziaEmail author
  • Jesse Provost
  • Alessandro Candreva
  • Maurizio Tamarasso
  • Francesco Maisano
  • Joachim M. Buhmann
Conference paper
  • 824 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11526)

Abstract

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.

Keywords

Mitral valve segmentation Echocardiography Neural network matrix factorization 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Luca Corinzia
    • 1
    Email author
  • Jesse Provost
    • 1
  • Alessandro Candreva
    • 2
  • Maurizio Tamarasso
    • 2
  • Francesco Maisano
    • 2
  • Joachim M. Buhmann
    • 1
  1. 1.Institute for Machine LearningETH ZurichZurichSwitzerland
  2. 2.Department of CardiologyUniversity Hospital ZurichZurichSwitzerland

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