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Multiview Machine Learning Using an Atlas of Cardiac Cycle Motion

  • Esther Puyol-Antón
  • Matthew Sinclair
  • Bernhard Gerber
  • Mihaela Silvia Amzulescu
  • Hélène Langet
  • Mathieu De Craene
  • Paul Aljabar
  • Julia A. Schnabel
  • Paolo Piro
  • Andrew P. King
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10663)

Abstract

A cardiac motion atlas provides a space of reference in which the cardiac motion fields of a cohort of subjects can be directly compared. From such atlases, descriptors can be learned for subsequent diagnosis and characterization of disease. Traditionally, such atlases have been formed from imaging data acquired using a single modality. In this work we propose a framework for building a multimodal cardiac motion atlas from MR and ultrasound data and incorporate a multiview classifier to exploit the complementary information provided by the two modalities. We demonstrate that our novel framework is able to detect non ischemic dilated cardiomyopathy patients from ultrasound data alone, whilst still exploiting the MR based information from the multimodal atlas. We evaluate two different approaches based on multiview learning to implement the classifier and achieve an improvement in classification performance from 77.5% to 83.50% compared to the use of US data without the multimodal atlas.

Keywords

Multimodal cardiac motion atlas Multiview dimensionality reduction Classification 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Esther Puyol-Antón
    • 1
  • Matthew Sinclair
    • 1
  • Bernhard Gerber
    • 3
  • Mihaela Silvia Amzulescu
    • 3
  • Hélène Langet
    • 2
    • 3
  • Mathieu De Craene
    • 2
  • Paul Aljabar
    • 1
  • Julia A. Schnabel
    • 1
  • Paolo Piro
    • 2
  • Andrew P. King
    • 1
  1. 1.Division of Imaging Sciences and Biomedical EngineeringKing’s College LondonLondonUK
  2. 2.Philips Research, MedisysParisFrance
  3. 3.Division of CardiologyCliniques Universitaires St-LucBrusselsBelgium

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