Automated segmentation of five different body tissues on computed tomography using deep learning.

Journal: Medical physics
PMID: 36008356

Abstract

PURPOSE: To develop and validate a computer tool for automatic and simultaneous segmentation of five body tissues depicted on computed tomography (CT) scans: visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), intermuscular adipose tissue (IMAT), skeletal muscle (SM), and bone.

Authors

  • Lucy Pu
    Department, of Cardiothoracic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
  • Naciye S Gezer
    Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
  • Syed F Ashraf
    North Allegheny Senior High School, Wexford, USA.
  • Iclal Ocak
    Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
  • Daniel E Dresser
    Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
  • Rajeev Dhupar
    Department of Cardiothoracic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pa; VA Pittsburgh Healthcare System, Pittsburgh, Pa. Electronic address: dhuparr2@upmc.edu.

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