Body mass classification from skeletal elements using landmark-free morphological atlas estimation with diffeomorphic shape mapping
Body mass classification from skeletal elements using landmark-free morphological atlas estimation with diffeomorphic shape mapping
复制标题
使用具有微分同形形状映射的无地标形态图谱估计对骨骼元素进行体重分类
DOI：
10.1117/12.2655795
复制
发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Zbijewski, Wojciech
中科院分区：
文献类型：
--
作者：
Li, Heyuan;Shi, Gengxin;Meckel, Lauren;Cunningham, Deborah;Wescott, Daniel J.;Sylvester, Adam D.;Charon, Nicolas;Zbijewski, Wojciech
目的：研究股骨形态是否受体质量的影响。为了建立与肥胖相关的变形，我们提出了一种基于微分同形映射的图谱估计框架，该框架放宽了许多传统形状建模方法中常见的点对应要求。方法：研究样本包括18名正常体重(BMI在20-25之间)和18名肥胖(BMI和GT；30)个体的股骨(德克萨斯州立大学捐赠的骨骼收藏)。骨表面模型(2,500个顶点和大约5,000个面)由样本(512x512矩阵，0.625x0.625x0.5 mm体素)的CT扫描生成。表面模型被输入到优化算法，该算法产生形状可变性的图谱表示，该图谱表示由平均骨模板和将模板匹配到每个试件上的不同形态变形组成。在支持向量机分类器的留一实验中，建立了正常体重与肥胖的主要图谱变形模式分类的准确率。结果：留一支持向量机实验获得了75%的分类准确率，表明功能性骨骼适应增加的体质量的可能性。通过可视化支持向量机分类方向给出的骨表面变形，我们发现与肥胖相关的形态改变可能包括股骨颈和粗隆相对增厚，以及股骨头后倾。结论：无标志性图谱估计算法能够检测到可能预测体重增加的股骨形态变异。
Purpose: We investigate whether femur morphology is affected by body mass (BM). To establish deformations associated with obesity, we propose an atlas estimation framework based on diffeomorphic shape mapping that relaxes the point correspondence requirement common to many conventional shape modeling approaches.Methods: The study sample consisted of femora from 18 normal weight (BMI between 20-25) and 18 obese (BMI > 30) individuals (Texas State University Donated Skeletal Collection). Bone surface models (2,500 vertices and approximately 5,000 faces) were generated from CT scans of the specimens (512x512 matrix, 0.625x0.625x0.5 mm voxels). The surface models were input to an optimization algorithm that yielded an atlas representation of shape variability consisting of a mean bone template and diffeomorphic deformations matching the template onto each specimen. The accuracy of normal weight vs. obese classification using principal atlas deformation modes was established in leave-one-out experiments with Support Vector Machine (SVM) classifier.Results: We achieved 75% classification accuracy in leave-one-out SVM experiments, indicating the possibility of functional skeletal adaptations to increased body mass. By visualizing the bone surface deformation given by the SVM classification direction, we found that morphological alterations associated with obesity might include relative thickening of the femoral neck and the trochanters, and retroversion of the femoral head.Conclusions: The landmark-free atlas estimation algorithm enabled detection of morphological femur variants that might be predictive of elevated body mass.
使用骨形状和关节空间变异性的关节统计模型对膝骨关节炎进行无地标形态测量分析
影响因子：
2.4
作者：
N. Charon;Amanul Islam;W. Zbijewski
通讯作者：
W. Zbijewski