A deep learning-based method for the diagnosis of vertebral fractures on spine MRI: retrospective training and validation of ResNet.

Journal: European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
Published Date: Aug 1, 2022

Abstract

PURPOSE: To improve the performance of less experienced clinicians in the diagnosis of benign and malignant spinal fracture on MRI, we applied the ResNet50 algorithm to develop a decision support system.

Authors

  • Lee-Ren Yeh
    Department of Radiology, E-Da Hospital, I-Shou University, Kaohsiung, Taiwan.
  • Yang Zhang
    Innovative Institute of Chinese Medicine and Pharmacy, Academy for Interdiscipline, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
  • Jeon-Hor Chen
    Department of Radiology, E-Da Hospital and I-Shou University, Kaohsiung 82445, Taiwan and Tu and Yuen Center for Functional Onco-Imaging and Department of Radiological Science, University of California, Irvine, California 92697.
  • Yan-Lin Liu
    Department of Radiological Sciences, University of California, 164 Irvine Hall, Irvine, CA, 92697-5020, USA.
  • An-Chi Wang
    Department of Radiology, Chi-Mei Medical Center, Tainan, Taiwan.
  • Jie-Yu Yang
    Department of Radiology, Chi-Mei Medical Center, Tainan, Taiwan.
  • Wei-Cheng Yeh
    Department of Radiology, E-Da Cancer Hospital, Kaohsiung, Taiwan.
  • Chiu-Shih Cheng
    Department of Radiology, E-Da Hospital and I-Shou University, Kaohsiung, Taiwan.
  • Li-Kuang Chen
    Department of Radiological Sciences, University of California, 164 Irvine Hall, Irvine, CA, 92697-5020, USA.
  • Min-Ying Su
    Department of Radiological Sciences, University of California, Irvine, CA 92697, USA.

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