A hierarchical fusion strategy of deep learning networks for detection and segmentation of hepatocellular carcinoma from computed tomography images.

Journal: Cancer imaging : the official publication of the International Cancer Imaging Society
PMID: 38532511

Abstract

BACKGROUND: Automatic segmentation of hepatocellular carcinoma (HCC) on computed tomography (CT) scans is in urgent need to assist diagnosis and radiomics analysis. The aim of this study is to develop a deep learning based network to detect HCC from dynamic CT images.

Authors

  • I-Cheng Lee
    Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.
  • Yung-Ping Tsai
    Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
  • Yen-Cheng Lin
    Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
  • Ting-Chun Chen
    Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
  • Chia-Heng Yen
    Institute of Computer Science and Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan.
  • Nai-Chi Chiu
    Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan.
  • Hsuen-En Hwang
    Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan.
  • Chien-An Liu
    Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan.
  • Jia-Guan Huang
    National Taiwan University School of Medicine, Taipei, Taiwan.
  • Rheun-Chuan Lee
    Department of Radiology, Taipei Veterans General Hospital, Taipei, Taiwan.
  • Yee Chao
    Cancer Center, Taipei Veterans General Hospital, Taipei, Taiwan.
  • Shinn-Ying Ho
  • Yi-Hsiang Huang
    Division of Gastroenterology and Hepatology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan. yhhuang@vghtpe.gov.tw.

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