Automatic liver segmentation and assessment of liver fibrosis using deep learning with MR T1-weighted images in rats.

Journal: Magnetic resonance imaging
Published Date: Dec 24, 2023

Abstract

OBJECTIVES: To validate the performance of nnU-Net in segmentation and CNN in classification for liver fibrosis using T1-weighted images.

Authors

  • Wenjing Zhang
    Department of Pharmacy, Shanghai Changhai Hospital, Naval Medical University, Shanghai, People's Republic of China.
  • Nan Zhao
    CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
  • Yuanxiang Gao
    Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China.
  • Baoxiang Huang
    Guangdong Medical University, Dongguan 523808, China.
  • Lili Wang
    School of Logistics, Chengdu University of Information Technology, Chengdu, China.
  • Xiaoming Zhou
    a Department of Pathology, Guangzhou Medical University, Guangzhou, Guangdong Province, China.
  • Zhiming Li
    Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, China. Electronic address: lizhiming@qdu.edu.cn.

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