Deep learning-assisted screening and diagnosis of scoliosis: segmentation of bare-back images via an attention-enhanced convolutional neural network.

Journal: Journal of orthopaedic surgery and research
PMID: 39953540

Abstract

BACKGROUND: Traditional diagnostic tools for scoliosis screening necessitate a substantial number of specialized personnel and equipment, leading to inconvenience that can result in missed opportunities for early diagnosis and optimal treatment. We have developed a deep learning-based image segmentation model to enhance the efficiency of scoliosis screening.

Authors

  • Xingyu Duan
    Department of Orthopedics, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, 750004, China.
  • Xiaojun Ma
    Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
  • Mengqi Zhu
    Department of Orthopedics, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, 750004, China.
  • Linan Wang
    Shanghai Health Development Research Center, Room 804, No 1477, West Beijing Road, Jing'an District, Shanghai, 20040, China. wanglinan@51mch.com.
  • Dingqi You
    Department of Spinal Cord Surgery, Henan Provincial People's Hospital, Zhengzhou, Henan, 450000, China.
  • Lili Deng
    Anhui Province Key Laboratory of Respiratory Tumor and Infectious Disease, First Affiliated Hospital of Bengbu Medical University, Bengbu, China.
  • Ningkui Niu
    Department of Orthopedics, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, 750004, China. niuningkui@163.com.

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