A Deep Learning Workflow for Mass-Forming Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma Classification Based on MRI.

Journal: Current oncology (Toronto, Ont.)
PMID: 36661691

Abstract

OBJECTIVE: Precise classification of mass-forming intrahepatic cholangiocarcinoma (MF-ICC) and hepatocellular carcinoma (HCC) based on magnetic resonance imaging (MRI) is crucial for personalized treatment strategy. The purpose of the present study was to differentiate MF-ICC from HCC applying a novel deep-learning-based workflow with stronger feature extraction ability and fusion capability to improve the classification performance of deep learning on small datasets.

Authors

  • Yangling Liu
    Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650504, China.
  • Bin Wang
    State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China; New South Wales Department of Primary Industries, Wagga Wagga Agricultural Institute, Wagga Wagga 2650, Australia. Electronic address: bin.a.wang@dpi.nsw.gov.au.
  • Xiao Mo
    School of Biomedical Engineering, Capital Medical University, Beijing 100069, China.
  • Kang Tang
    Department of Radiology, Second Affiliated Hospital of Kunming Medical University, Kunming 650101, China.
  • Jianfeng He
    Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China.
  • Jingang Hao
    Department of Radiology, Second Affiliated Hospital of Kunming Medical University, Kunming 650101, China.

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