The knowledge distillation-assisted multimodal model for osteoporosis screening.

Journal: Computer methods and programs in biomedicine
Published Date: May 22, 2025

Abstract

BACKGROUND AND OBJECTIVE: Osteoporosis is characterized by reduced bone mass and deterioration of bone structure, yet screening rates prior to fractures remain low. Given its high prevalence and severe consequences, developing an effective osteoporosis screening model is highly significant. However, constructing these screening models presents two main challenges. First, selecting representative slices from CT image sequences is challenging, making it crucial to filter the most indicative slices. Second, samples lacking complete modal data cannot be directly used in multimodal fusion, resulting in underutilization of available data and limiting the performance of the multimodal osteoporosis screening model.

Authors

  • Teng Su
    School of Control Science and Engineering, Shandong University, Jinan, Shandong, China, 250061.
  • Qing Yang
    School of Nursing, Chengdu Medical College, Chengdu, China.
  • Meng Si
    Department of Orthopedics, Qilu Hospital of Shandong University, Jinan, Shandong, China, 250000.
  • Yuanyuan Sun
    School of Computer Science and Technology, Dalian University of Technology, Dalian, China.
  • Xinyu Ji
    Department of Thoracic Surgery, The First Hospital of China Medical University, Liaoning, Shenyang, China.
  • Yuyan Zhang
    College of Life Science, Zhejiang Chinese Medical University, Hangzhou, China.
  • Bing Ji
    School of Control Science and Engineering, Shandong University, Jinan, Shandong, China.

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