Automatic localization and deep convolutional generative adversarial network-based classification of focal liver lesions in computed tomography images: A preliminary study.

Journal: Journal of gastroenterology and hepatology
PMID:

Abstract

BACKGROUND AND AIM: Computed tomography of the abdomen exhibits subtle and complex features of liver lesions, subjectively interpreted by physicians. We developed a deep learning-based localization and classification (DLLC) system for focal liver lesions (FLLs) in computed tomography imaging that could assist physicians in more robust clinical decision-making.

Authors

  • Pushpanjali Gupta
    Division of Translational Research, Taipei Veterans General Hospital, Taipei, Taiwan.
  • Yao-Chun Hsu
    Division of Gastroenterology and Hepatology, E-Da Hospital, Kaohsiung, Taiwan.
  • Li-Lin Liang
    Health Innovation Center, National Yang Ming Chiao Tung University, Taipei, Taiwan.
  • Yuan-Chia Chu
    Information Management Office, Taipei Veterans General Hospital, Taipei, Taiwan.
  • Chia-Sheng Chu
    Ph.D. Program of Interdisciplinary Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
  • Jaw-Liang Wu
    School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
  • Jian-An Chen
    Department of Organ Transplantation, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282, China.
  • Wei-Hsiu Tseng
    Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, Taiwan.
  • Ya-Ching Yang
    Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, Taiwan.
  • Teng-Yu Lee
    Division of Gastroenterology and Hepatology, Taichung Veterans General Hospital, Taichung, Taiwan.
  • Che-Lun Hung
    Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, Taiwan; Department of Computer Science and Communication Engineering, Providence University, Taichung, Taiwan.
  • Chun-Ying Wu
    Division of Translational Research, Taipei Veterans General Hospital, Taipei, Taiwan.