Transfer learning for data-efficient abdominal muscle segmentation with convolutional neural networks.

Journal: Medical physics
Published Date: Feb 28, 2022

Abstract

BACKGROUND: Skeletal muscle segmentation is an important procedure for assessing sarcopenia, an emerging imaging biomarker of patient frailty. Data annotation remains the bottleneck for training deep learning auto-segmentation models.

Authors

  • Dónal M McSweeney
    Division of Cancer Sciences, University of Manchester, Manchester, UK.
  • Edward G Henderson
    Division of Cancer Sciences, University of Manchester, Manchester, UK.
  • Marcel van Herk
    Manchester Cancer Research Centre, Division of Molecular and Clinical Cancer Science, School of Medical Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Sciences Centre, UK; The Christie NHS Foundation Trust, Manchester Academic Health Sciences Centre, UK.
  • Jamie Weaver
    Department of Medical Oncology, The Christie Hospital NHS Foundation Trust, Manchester, UK.
  • Paul A Bromiley
    Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester, UK.
  • Andrew Green
    Department of Cellular Pathology, University of Nottingham, Nottingham, UK.
  • Alan McWilliam
    Division of Cancer Sciences, University of Manchester, Manchester, UK.

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