Using deep learning models in magnetic resonance cholangiopancreatography images to diagnose common bile duct stones.

Journal: Scandinavian journal of gastroenterology
PMID: 37712446

Abstract

BACKGROUNDS AND AIMS: Magnetic resonance cholangiopancreatography (MRCP) plays a significant role in diagnosing common bile duct stones (CBDS). Currently, there are no studies to detect CBDS by using the deep learning (DL) model in MRCP. This study aimed to use the DL model You Only Look Once version 5 (YOLOv5) to diagnose CBDS in MRCP images and verify its validity compared to the accuracy of radiologists.

Authors

  • Bo Luo
    School of mechanical science and engineering, Huazhong University of Science and Technology, Luoyu Road 1037, 430074, Wuhan, China.
  • Zhiyuan Li
    School of Clinical Medicine, General Hospital of Ningxia Medical University, Yinchuan, China.
  • Ke Zhang
    Center for Radiation Oncology, Affiliated Hangzhou Cancer Hospital, Zhejiang University School of Medicine, Hangzhou 310001, China.
  • Sikai Wu
    Department of Hepatobiliary and Vascular Surgery, The First Affiliated Hospital, School of Clinical Medicine, Chengdu Medical College, Chengdu, Sichuan Province, P. R. China.
  • Weiwei Chen
    Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center affiliated to Shanghai Jiaotong University School of Medicine, Ministry of Education-Shanghai Key Laboratory of Children's Environmental Health, Shanghai, China.
  • Ning Fu
    Department of Hepatobiliary and Vascular Surgery, The First Affiliated Hospital, School of Clinical Medicine, Chengdu Medical College, Chengdu, Sichuan Province, P. R. China.
  • Zhiming Yang
    Shenzhen Baoan Authentic TCM Therapy Hospital, Shenzhen, 518101, China.
  • Jingcheng Hao
    Department of Hepatobiliary and Vascular Surgery, The First Affiliated Hospital, School of Clinical Medicine, Chengdu Medical College, Chengdu, Sichuan Province, P. R. China.

Keywords

External Resources

Popular Topics
Recent Journals