Abstract This paper proposes a biomechanical performance design method of joint prosthesis for medical rehabilitation via Generative Structure Optimization (GSO). Firstly, the 3D reconstruction of manifold structure involving hard bone and cartilage is sequentially and progressively implemented from heterogeneous medical images such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) via iteration. On the basis of reconstructed mesh structure, the finite element method (FEM) is hereby employed to verify the structure by evaluating the mechanical force distribution. The biomechanical performance design model for 3 D printing (3DP) is then built using multi-objective optimization (MOO) by considering adaptive layer thickness, infill patterns and infill trajectories, etc. The GSO outlets a generative data-driven system which covers various stages such as personalized CT, subsequent 3 D reconstruction, further finite element analysis (FEA) and even structural parameter optimization. The physical experiment of Additive manufacturing (AM) proves that, the relative density, surface topography and wear-resisting performance of joint prosthesis can be improved by GSO which helps to improve biomechanical performance, including kinematics and dynamics. The proposed method may arouse the huge attention in the prosthesis applications to promote patients’ high-end customization well-being.

中文翻译：

---

基于生成结构优化的医疗康复关节假体生物力学性能设计

摘要 本文提出了一种基于生成结构优化（GSO）的医疗康复关节假体生物力学性能设计方法。首先，涉及硬骨和软骨的流形结构的 3D 重建是通过迭代从异构医学图像，如计算机断层扫描 (CT) 和磁共振成像 (MRI) 中依次逐步实现的。在重建网格结构的基础上，采用有限元法（FEM）通过评估机械力分布来验证结构。然后，通过考虑自适应层厚度、填充图案和填充轨迹等，使用多目标优化 (MOO) 构建 3D 打印 (3DP) 的生物力学性能设计模型。GSO 输出一个生成数据驱动系统，涵盖各个阶段，如个性化 CT、后续 3D 重建、进一步的有限元分析 (FEA) 甚至结构参数优化。增材制造（AM）的物理实验证明，GSO可以改善关节假体的相对密度、表面形貌和耐磨性能，有助于改善生物力学性能，包括运动学和动力学。所提出的方法可能会引起假肢应用的巨大关注，以促进患者的高端定制福祉。GSO 可以改善关节假体的表面形貌和耐磨性能，这有助于改善生物力学性能，包括运动学和动力学。所提出的方法可能会引起假肢应用的巨大关注，以促进患者的高端定制福祉。GSO 可以改善关节假体的表面形貌和耐磨性能，这有助于改善生物力学性能，包括运动学和动力学。所提出的方法可能会引起假肢应用的巨大关注，以促进患者的高端定制福祉。