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Interactive Graph-Cut Segmentation for Fast Creation of Finite Element Models from Clinical CT Data for Hip Fracture Prediction

机译：从临床CT数据快速创建有限元模型的交互式图割分割用于髋部骨折预测

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摘要

In this study, we propose interactive graph cut image segmentation for fast creation of femur finite element (FE) models from clinical computed tomography scans for hip fracture prediction. Using a sample of N=48 bone scans representing normal, osteopenic and osteoporotic subjects, the proximal femur was segmented using manual (gold standard) and graph cut segmentation. Segmentations were subsequently used to generate FE models to calculate overall stiffness and peak force in a sideways fall simulations. Results show that, comparable FE results can be obtained with the graph cut method, with a reduction from 20 minutes to 2–5 minutes interaction time. Average differences between segmentation methods of 0.22 mm were not significantly correlated with differences in FE derived stiffness (R2 = 0.08, p = 0.05) and weakly correlated to differences in FE derived peak force (R2 = 0.16, p = 0.01). We further found that changes in automatically assigned boundary conditions as a consequence of small segmentation differences were significantly correlated with FE derived results. The proposed interactive graph cut segmentation software MITK-GEM is freely available online at .
机译：在这项研究中，我们提出了交互式图形切割图像分割技术，可从临床CT扫描中快速创建股骨有限元（FE）模型，以预测髋部骨折。使用代表正常，骨质疏松和骨质疏松受试者的N = 48骨扫描样本，使用手动（金标准）和图形切割分割对股骨近端进行分割。随后将分段用于生成有限元模型，以在侧向跌落模拟中计算整体刚度和峰值力。结果表明，使用图形切割方法可以获得可比的有限元分析结果，交互时间从20分钟减少到2-5分钟。分割方法之间的平均差异0.22 mm与有限元衍生的刚度差异（R 2 = 0.08，p = 0.05）并不显着相关，而与有限元衍生的峰值力差异（R 2 = 0.16，p = 0.01）。我们进一步发现，由于小的分割差异而导致的自动分配边界条件的变化与FE得出的结果显着相关。拟议的交互式图形切割分割软件MITK-GEM可在上免费在线获得。

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