The three-dimensional weakly supervised deep learning algorithm for traumatic splenic injury detection and sequential localization: an experimental study.

Journal: International journal of surgery (London, England)
PMID: 36999810

Abstract

BACKGROUND: Splenic injury is the most common solid visceral injury in blunt abdominal trauma, and high-resolution abdominal computed tomography (CT) can adequately detect the injury. However, these lethal injuries sometimes have been overlooked in current practice. Deep learning (DL) algorithms have proven their capabilities in detecting abnormal findings in medical images. The aim of this study is to develop a three-dimensional, weakly supervised DL algorithm for detecting splenic injury on abdominal CT using a sequential localization and classification approach.

Authors

  • Chi-Tung Cheng
    Department of Trauma and Emergency Surgery, Chang Gung Memorial Hospital, Linkou, Chang Gung University, Taoyuan, Taiwan.
  • Hou-Shian Lin
    Department of Trauma and Emergency Surgery, Chang Gung Memorial Hospital, Linkou ; Chang Gung University, Taoyuan, Taiwan.
  • Chih-Po Hsu
    Department of Trauma and Emergency Surgery, Chang Gung Memorial Hospital, Linkou ; Chang Gung University, Taoyuan, Taiwan.
  • Huan-Wu Chen
    Division of Emergency and Critical Care Radiology, Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Taoyuan, Taiwan.
  • Jen-Fu Huang
    Department of Trauma and Emergency Surgery.
  • Chih-Yuan Fu
    Department of Trauma and Emergency Surgery.
  • Chi-Hsun Hsieh
    Department of Trauma and Emergency Surgery, Chang Gung Memorial Hospital, Linkou, Chang Gung University, Taoyuan, Taiwan.
  • Chun-Nan Yeh
    Department of Surgery, Chang Gung Memorial Hospital, Linkou, Chang Gung University, Taoyuan, Taiwan.
  • I-Fang Chung
    Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan.
  • Chien-Hung Liao
    Department of Trauma and Emergency Surgery, Chang Gung Memorial Hospital, Linkou, Chang Gung University, Taoyuan, Taiwan. surgymet@gmail.com.

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