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Real-time reconstruction of 3D bone models via very-low-dose protocols

  • Yiqun Lin
  • , Haoran Sun
  • , Yongqing Li
  • , Rabia Aslam
  • , Lung Fung Tse
  • , Tiange Cheng
  • , Chun Sing Chui
  • , Wing Fung Yau
  • , Victorine R. Le Meur
  • , Meruyert Amangeldy
  • , Kiho Cho
  • , Yinyu Ye
  • , James Zou
  • , Wei Zhao*
  • , Xiaomeng Li*
  • *此作品的通讯作者
  • Hong Kong University of Science and Technology
  • Koln 3D Technology (Medical) Limited
  • Beihang University
  • Union Hospital
  • The University of Hong Kong
  • Chinese University of Hong Kong
  • Stanford University
  • Tianmushan Laboratory

科研成果: 期刊稿件文章同行评审

摘要

Patient-specific bone models are essential for designing surgical guides and preoperative planning, as they enable the visualization of intricate anatomical structures. However, traditional CT-based approaches for creating bone models are limited to preoperative use due to the low flexibility and high radiation exposure of CT and time-consuming manual delineation. Here, we introduce Semi-Supervised Reconstruction with Knowledge Distillation (SSR-KD), a fast and accurate AI framework to reconstruct high-quality bone models from biplanar X-rays in 30 seconds, with an average error under 1.0 mm, eliminating the dependence on CT and manual work. Additionally, high tibial osteotomy simulation was performed by experts on reconstructed bone models, demonstrating that bone models reconstructed from biplanar X-rays have comparable clinical applicability to those annotated from CT. Overall, our approach accelerates the process, reduces radiation exposure, enables intraoperative guidance, and significantly improves the practicality of bone models, offering transformative applications in orthopedics.

源语言英语
文章编号353
期刊npj Digital Medicine
9
1
DOI
出版状态已出版 - 12月 2026

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