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Beyond the AHA 17-Segment Model: Motion-Driven Parcellation of the Left Ventricle

  • Wenjia Bai
  • Devis Peressutti
  • Sarah Parisot
  • Ozan Oktay
  • Martin Rajchl
  • Declan O’Regan
  • Stuart Cook
  • Andrew King
  • Daniel Rueckert
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9534)

Abstract

A major challenge for cardiac motion analysis is the high-dimensionality of the motion data. Conventionally, the AHA model is used for dimensionality reduction, which divides the left ventricle into 17 segments using criteria based on anatomical structures. In this paper, a novel method is proposed to divide the left ventricle into homogeneous parcels in terms of motion trajectories. We demonstrate that the motion-driven parcellation has good reproducibility and use it for data reduction and motion description on a dataset of 1093 subjects. The resulting motion descriptor achieves high performance on two exemplar applications, namely gender and age predictions. The proposed method has the potential to be applied to groupwise motion analysis.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Wenjia Bai
    • 1
  • Devis Peressutti
    • 2
  • Sarah Parisot
    • 1
  • Ozan Oktay
    • 1
  • Martin Rajchl
    • 1
  • Declan O’Regan
    • 3
  • Stuart Cook
    • 3
    • 4
  • Andrew King
    • 2
  • Daniel Rueckert
    • 1
  1. 1.Biomedical Image Analysis Group, Department of ComputingImperial College LondonLondonUK
  2. 2.Division of Imaging Sciences and Biomedical EngineeringKing’s College LondonLondonUK
  3. 3.MRC Clinical Sciences Centre, Hammersmith HospitalImperial College LondonLondonUK
  4. 4.Duke-NUS Graduate Medical SchoolSingaporeSingapore

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