Robust Multi-View Fracture Detection in the Presence of Other Abnormalities Using HAMIL-Net.

Journal: Military medicine
Published Date: Nov 8, 2023

Abstract

INTRODUCTION: Foot and ankle fractures are the most common military health problem. Automated diagnosis can save time and personnel. It is crucial to distinguish fractures not only from normal healthy cases, but also robust against the presence of other orthopedic pathologies. Artificial intelligence (AI) deep learning has been shown to be promising. Previously, we have developed HAMIL-Net to automatically detect orthopedic injuries for upper extremity injuries. In this research, we investigated the performance of HAMIL-Net for detecting foot and ankle fractures in the presence of other abnormalities.

Authors

  • Xing Lu
    Zhuhai Sanmed Biotech Ltd, Zhuhai, Guangdong, China.
  • Eric Y Chang
    Department of Radiology, University of California San Diego, San Diego, CA, 92093, USA.
  • Jiang Du
    Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • An Yan
    University of California, San Diego, La Jolla, CA 92093, USA.
  • Julian McAuley
    Department of Computer Science and Engineering, University of California, San Diego, La Jolla, California.
  • Amilcare Gentili
    San Diego VA Health Care System, San Diego, CA, USA.
  • Chun-Nan Hsu
    University of California San Diego, La Jolla, CA.

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