Improved brain metastases segmentation using generative adversarial network and conditional random field optimization mask R-CNN.

Journal: Medical physics
Published Date: May 22, 2024

Abstract

BACKGROUND: In radiotherapy, the delineation of the gross tumor volume (GTV) in brain metastases using computed tomography (CT) simulation localization is very important. However, despite the criticality of this process, a pronounced gap exists in the availability of tools tailored for the automatic segmentation of the GTV based on CT simulation localization images.

Authors

  • Yiren Wang
    Department of Electrical and Computer Engineering, University of Washington, 98195, Seattle, WA, USA. ethanwyr@uw.edu.
  • Zhongjian Wen
    School of Nursing, Southwest Medical University, Luzhou, China.
  • Lei Su
    Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China.
  • Hairui Deng
    School of Nursing, Southwest Medical University, Luzhou, Sichuan, China.
  • Jiali Gong
  • Hongli Xiang
    School of Nursing, Southwest Medical University, Luzhou, Sichuan, China.
  • Yongcheng He
    Department of Pharmacy, College of Veterinary Medicine, Sichuan Agricultural University, Chengdu, Sichuan, China.
  • Huaiwen Zhang
    Department of Radiotherapy, Jiangxi Cancer Hospital, The Second Affiliated Hospital of Nanchang Medical College, Jiangxi Clinical Research Center for Cancer, Nanchang, China.
  • Ping Zhou
  • Haowen Pang
    Department of Oncology, The Affiliated Hospital of Southwest Medical University, Sichuan, China.

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