肘关节假体设计数据

滤波反投影算法是通过CT扫描获取人体解剖数据的一种方法，通过本算法得到的人体解剖数据，再将数据进行去噪、分割、渲染等后处理操作，以便更好地呈现和分析重建结果。通过CT数据的X Y Z三维坐标、最小/ 最大灰度值、层距、 CT矩阵大小、Focal Spot(s)等参数可以计算出重建三维数据所需的曲率半径，从而得出人体骨骼解剖数据，进而设计出符合国人骨骼特征的肘关节假体，应用于临床上肘关节置换手术。该算法以解决现有的肘关节假体设计源于西方人种解剖特点设计的，假体植入国人体内不匹配的问题。三维图像的后处理：对三维图像进行去噪、分割、渲染等后处理操作，能更好地呈现和分析重建结果。通过该算法能分析出人体骨骼解剖数据，以设计出符合国人骨骼特征的肘关节假体产品。曲率半径是重要的产品设计参数，能反映曲面上点的几何性质，是曲率的倒数。对于三维重建的离散数据，曲率半径通常用离散平均曲率半径来表示，可通过计算离散平均曲率来求取。离散平均曲率计算通过引入Laplace-Beltrami算子△=2H×n和曲面的平均曲面流形，以目标顶点到相邻的所有顶点向量加权和，乘以目标顶点与所有相邻顶点组成的三角形法向量平均值，得到离散平均曲率，将1除以离散平均曲率得到离散平均曲率半径。根据产品设计需求，由有经验的技术员按每5mm取一点共选择3个特征点的离散平均曲率半径记为曲率半径R1、R2、R3。

Filtered Back Projection (FBP) algorithm is a method for acquiring human anatomical data via CT scanning. Human anatomical data obtained through this algorithm undergo post-processing operations such as denoising, segmentation, and rendering to better present and analyze the reconstruction results. Parameters including XYZ three-dimensional coordinates, minimum/maximum gray values, slice thickness, CT matrix size, and Focal Spot(s) of CT data can be used to calculate the radius of curvature required for 3D data reconstruction, thereby deriving human skeletal anatomical data, and then designing elbow joint prosthetics that conform to the skeletal characteristics of the Chinese population for application in clinical elbow replacement surgeries. This algorithm addresses the issue that existing elbow joint prosthetics are designed based on the anatomical characteristics of Western populations, leading to mismatches when implanted in Chinese patients.

Post-processing of 3D images: Performing post-processing operations such as denoising, segmentation, and rendering on 3D images enables better presentation and analysis of reconstruction results. This algorithm can analyze human skeletal anatomical data to design elbow joint prosthetic products that conform to the skeletal characteristics of the Chinese population.

The radius of curvature is an important product design parameter, which reflects the geometric properties of points on a curved surface and is the reciprocal of curvature. For discrete data from 3D reconstruction, the radius of curvature is usually represented by the discrete mean curvature radius, which can be obtained by calculating the discrete mean curvature. The calculation of discrete mean curvature is performed by introducing the Laplace-Beltrami operator △=2H×n and the mean surface manifold of the curved surface: the discrete mean curvature is obtained by taking the weighted sum of the vectors from the target vertex to all adjacent vertices, multiplying it by the average of the normal vectors of the triangles formed by the target vertex and all adjacent vertices, and the discrete mean curvature radius is obtained by dividing 1 by the discrete mean curvature. According to product design requirements, experienced technicians select 3 feature points by taking a point every 5mm, and the discrete mean curvature radii of these points are recorded as curvature radii R1, R2, and R3.