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Model Generation from Imaging Data for Simulation in Biomechanics

机译:从成像数据生成模型以进行生物力学仿真

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There has been increasing interest in the generation of models appropriate for computational simulations -Finite Element Analysis (FEA) and Computational Fluid Dynamics (CFD) - from biomedical imaging data. Novel methods of generating the required volume discretizations directly and robustly from the image data have been proposed however there are a range of issues related to image processing and mesh generation which still need to be addressed. The paper will present issues specific to image-based meshing, in particular techniques for the generation and handling of appropriately anti-aliased multi-part image masks for producing accurate models from surface and volume reconstruction techniques. Two case studies will be presented, including the model generation of a hip implant by merging image and CAD data, and the pressure response in head impacts.
机译:从生物医学成像数据产生适合于计算仿真的模型(有限元分析(FEA)和计算流体动力学(CFD))的兴趣日益浓厚。已经提出了从图像数据直接且鲁棒地生成所需的体积离散的新颖方法,但是仍然存在与图像处理和网格生成相关的一系列问题。本文将介绍特定于基于图像的网格划分的问题,特别是用于生成和处理适当抗锯齿的多部分图像蒙版的技术,这些蒙版用于从表面和体积重建技术中生成准确的模型。将提供两个案例研究,包括通过合并图像和CAD数据生成髋关节植入物的模型,以及头部撞击时的压力响应。

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