Automatic Segmentation of the Prostate on CT Images Using Deep Neural Networks (DNN).

Journal: International journal of radiation oncology, biology, physics
Published Date: Mar 16, 2019

Abstract

PURPOSE: Recent advances in deep neural networks (DNNs) have unlocked opportunities for their application for automatic image segmentation. We have evaluated a DNN-based algorithm for automatic segmentation of the prostate gland on a large cohort of patient images.

Authors

  • Chang Liu
    Key Lab of Cell Differentiation and Apoptosis of Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Stephen J Gardner
    Department of Radiation Oncology, Josephine Ford Cancer Institute, Henry Ford Health System, Detroit, Michigan.
  • Ning Wen
    Department of Radiation Oncology, Henry Ford Hospital, Detroit, Michigan, USA.
  • Mohamed A Elshaikh
    Department of Radiation Oncology, Josephine Ford Cancer Institute, Henry Ford Health System, Detroit, Michigan.
  • Farzan Siddiqui
    Department of Radiation Oncology, Josephine Ford Cancer Institute, Henry Ford Health System, Detroit, Michigan.
  • Benjamin Movsas
    Department of Radiation Oncology, Josephine Ford Cancer Institute, Henry Ford Health System, Detroit, Michigan.
  • Indrin J Chetty
    Department of Radiation Oncology, Henry Ford Hospital, Detroit, Michigan, USA.

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