标题： 基于非常低剂量协议的实时、基于人群的三维骨骼模型重建 显示英文标题

标题： Real-Time, Population-Based Reconstruction of 3D Bone Models via Very-Low-Dose Protocols

摘要： 患者特异性骨模型对于设计手术导板和术前规划至关重要，因为它们能够可视化复杂的解剖结构。 然而，传统的基于CT的骨模型创建方法由于CT的低灵活性、高辐射暴露和耗时的手动勾画，仅限于术前使用。 在此，我们引入了半监督重建知识蒸馏（SSR-KD），这是一种快速且准确的人工智能框架，可在30秒内从双平面X射线重建高质量的骨模型，平均误差低于1.0毫米，消除了对CT和手动工作的依赖。 此外，专家在重建的骨模型上进行了高位胫骨截骨模拟，结果表明，从双平面X射线重建的骨模型在临床适用性方面与从CT标注的模型相当。 总体而言，我们的方法加快了流程，减少了辐射暴露，实现了术中引导，并显著提高了骨模型的实用性，为骨科领域提供了变革性的应用。 显示英文摘要

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.