A new architecture combining convolutional and transformer-based networks for automatic 3D multi-organ segmentation on CT images.

Journal: Medical physics
Published Date: Sep 22, 2023

Abstract

PURPOSE: Deep learning-based networks have become increasingly popular in the field of medical image segmentation. The purpose of this research was to develop and optimize a new architecture for automatic segmentation of the prostate gland and normal organs in the pelvic, thoracic, and upper gastro-intestinal (GI) regions.

Authors

  • Chengyin Li
    College of Engineering - Dept. of Computer Science, Wayne State University, Detroit, Michigan, USA.
  • Hassan Bagher-Ebadian
    Department of Radiation Oncology, Henry Ford Hospital, Detroit, Michigan, USA.
  • Rafi Ibn Sultan
    College of Engineering - Dept. of Computer Science, Wayne State University, Detroit, Michigan, USA.
  • Mohamed Elshaikh
    Department of Radiation Oncology, Henry Ford Cancer Institute, Detroit, Michigan, USA.
  • Benjamin Movsas
    Department of Radiation Oncology, Josephine Ford Cancer Institute, Henry Ford Health System, Detroit, Michigan.
  • Dongxiao Zhu
  • Indrin J Chetty
    Department of Radiation Oncology, Henry Ford Hospital, Detroit, Michigan, USA.

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