A novel hybrid deep learning framework based on biplanar X-ray radiography images for bone density prediction and classification.

Journal: Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA
PMID: 39812675

Abstract

UNLABELLED: This study utilized deep learning for bone mineral density (BMD) prediction and classification using biplanar X-ray radiography (BPX) images from Huashan Hospital Medical Checkup Center. Results showed high accuracy and strong correlation with quantitative computed tomography (QCT) results. The proposed models offer potential for screening patients at a high risk of osteoporosis and reducing unnecessary radiation and costs.

Authors

  • Kun Zhou
    School of Mathematics Science, Peking University, Beijing, China.
  • Yuqi Zhu
    Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, NO. 7 Pengfei Road, Dapeng District, Shenzhen 518124, China.
  • Xiao Luo
    Department of Spine Surgery, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.
  • Shan Yang
    Clinic of Radiology and Nuclear Medicine, University Hospital Basel, Petersgraben 4, 4031, Basel, Switzerland.
  • Enhui Xin
    Academy for Engineering and Technology, Fudan University, Shanghai, China.
  • Yanwei Zeng
    Department of Radiology, Huashan Hospital, Fudan University, 12 Wulumuqi Middle Road, Shanghai 200040, China; Institute of Functional and Molecular Medical Imaging, Fudan University, 12 Wulumuqi Middle Road, Shanghai 200040, China.
  • Junyan Fu
    Department of Radiology, Huashan Hospital, Fudan University, Shanghai, 200040, China. Electronic address: 22111220057@m.fudan.edu.cn.
  • Zhuoying Ruan
    Department of Radiology, Huashan Hospital, Fudan University, 12 Wulumuqi Middle Road, Shanghai, 200040, China.
  • Rong Wang
    College of Food Science and Engineering, Northwest A&F University, Yangling 712100, Shanxi, China. Electronic address: wangrong91@nwsuaf.edu.cn.
  • Liqin Yang
    Academy for Engineering and Technology, Fudan University, Shanghai, China.
  • Daoying Geng
    Department of Radiology, Huashan Hospital, Fudan University, 12 Wulumuqi Rd. Middle, Shanghai, 200040, China. GengdaoyingGDY@163.com.

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