Automated segmentation of liver and hepatic vessels on portal venous phase computed tomography images using a deep learning algorithm.

Journal: Journal of applied clinical medical physics
PMID: 38773719

Abstract

BACKGROUND: CT-image segmentation for liver and hepatic vessels can facilitate liver surgical planning. However, time-consuming process and inter-observer variations of manual segmentation have limited wider application in clinical practice.

Authors

  • Shengwei Li
    Minimally Invasive Tumor Therapy Center, Beijing Hospital, Peking Union Medical College, Beijing, China.
  • Xiao-Guang Li
    Minimally Invasive Tumor Therapy Center, Beijing Hospital, Peking Union Medical College, Beijing, China.
  • Fanyu Zhou
    Minimally Invasive Tumor Therapy Center, Beijing Hospital, Peking Union Medical College, Beijing, China.
  • Yumeng Zhang
    Minimally Invasive Tumor Therapy Center, Beijing Hospital, Peking Union Medical College, Beijing, China.
  • Zhixin Bie
    Minimally Invasive Tumor Therapy Center, Beijing Hospital, Peking Union Medical College, Beijing, China.
  • Lin Cheng
    Department of Radiology, Southwest Hospital, Third Military Medical University (Army Military Medical University), Chongqing, China.
  • Jinzhao Peng
    Minimally Invasive Tumor Therapy Center, Beijing Hospital, Peking Union Medical College, Beijing, China.
  • Bin Li
    Department of Magnetic Resonance Imaging (MRI), Beijing Shijitan Hospital, Capital Medical University, Beijing, China.

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