Integrating manual annotation with deep transfer learning and radiomics for vertebral fracture analysis.

Journal: BMC medical imaging
PMID: 39915711

Abstract

BACKGROUND: Vertebral compression fractures (VCFs) are prevalent in the elderly, often caused by osteoporosis or trauma. Differentiating acute from chronic VCFs is vital for treatment planning, but MRI, the gold standard, is inaccessible for some. However, CT, a more accessible alternative, lacks precision. This study aimed to enhance CT's diagnostic accuracy for VCFs using deep transfer learning (DTL) and radiomics.

Authors

  • Jing Wang
    Endoscopy Center, Peking University Cancer Hospital and Institute, Beijing, China.
  • Zhirui Dong
    Department of Orthopaedic Surgery, Jinshan Hospital, Fudan University, Shanghai, China.
  • Huanxin He
    Department of Orthopaedic Surgery, Jinshan Hospital, Fudan University, Shanghai, China.
  • Zhiyang Gao
  • Yukai Huang
    Department of Orthopaedic Surgery, Jinshan Hospital, Fudan University, Shanghai, China.
  • Guangcheng Yuan
    Department of Orthopaedic Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
  • Libo Jiang
    College of Biological Sciences and Biotechnology, Beijing Forestry UniversityBeijing, China; Center for Computational Biology, Beijing Forestry UniversityBeijing, China.
  • Mingdong Zhao
    Department of Orthopaedic Surgery, Jinshan Hospital, Fudan University, Shanghai, China. zhao_mingdong@fudan.edu.cn.

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