ssVERDICT: Self-supervised VERDICT-MRI for enhanced prostate tumor characterization.

Journal: Magnetic resonance in medicine
Published Date: Jun 9, 2024

Abstract

PURPOSE: Demonstrating and assessing self-supervised machine-learning fitting of the VERDICT (vascular, extracellular and restricted diffusion for cytometry in tumors) model for prostate cancer.

Authors

  • Snigdha Sen
    University College London, UK.
  • Saurabh Singh
    Center for Medical Imaging, Division of Medicine, University College London, London, UK.
  • Hayley Pye
    Department of Targeted Intervention, Division of Surgery and Interventional Science, University College London, London, UK.
  • Caroline M Moore
    Division of Surgery and Interventional Science, University College London, London, UK.
  • Hayley C Whitaker
    Department of Targeted Intervention, Division of Surgery and Interventional Science, University College London, London, UK.
  • Shonit Punwani
    Centre for Medical Imaging, University College London, 2nd Floor Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK. shonit.punwani@gmail.com.
  • David Atkinson
    Centre for Medical Imaging, University College London, 2nd Floor Charles Bell House, 43-45 Foley Street, London, W1W 7TS, UK.
  • Eleftheria Panagiotaki
    Center for Medical Image Computing, Department of Computer Science, University College London, London, UK.
  • Paddy J Slator
    University College London, UK.

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