用双平面X光30秒生成误差小于1毫米的骨模型，无需CT和人工标注。
Real-Time Reconstruction of 3D Bone Models via Very-Low-Dose Protocols
- 基于知识蒸馏的半监督学习，从双平面X光重建3D骨模型。
- 平均误差低于1.0毫米，重建耗时仅30秒。
- 适合术中实时导航，大幅降低辐射且提升临床实用性。
个性化骨模型对设计手术导板和术前规划至关重要，可清晰展现复杂解剖结构。然而，传统基于CT的方法受限于灵活性差、辐射高及人工勾画耗时，仅适用于术前。本文提出半监督重建与知识蒸馏框架（SSR-KD），可在30秒内从双平面X射线快速生成高质量骨模型，平均误差低于1.0毫米，彻底摆脱对CT和人工操作的依赖。专家在重建模型上完成了高位胫骨截骨模拟，结果表明其临床适用性与基于CT标注的模型相当。整体上，该方法加速流程、减少辐射、支持术中引导，显著提升骨模型实用性，在骨科领域具有变革性应用前景。
原文摘要 · Abstract (English)
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.
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