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Robust Image-Based Modeling and Simulation in Biomechanics

机译:生物力学中基于图像的鲁棒建模与仿真

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摘要

Image-based modeling and simulation has become an important analytic and predictive tool for patient-specific medical applications, including large-scale in silico patient studies, optimized medical device design, and custom surgical guides and implants via additive manufacturing. The pipeline for patient-specific modeling and simulation is: image acquisition, image segmentation, surface generation, mesh generation, physics-based modeling and simulation, and clinical application. This research establishes a semi-automatic workflow for these steps, which includes a novel image-based meshing tool Shabaka. The toolchain is demonstrated by modeling the mechanics of a beating human heart based on magnetic resonance imaging (MRI) data.;The Shabaka workflow ensures robust execution of each step of the pipeline. Medical images are processed and segmented using thresholding, region-growing, and manual techniques. Watertight surface meshes are extracted from image masks using a novel Voronoi-based algorithm. For scientific computing purposes, surface meshes are supplied either to tetrahedral meshing routines for conventional finite element approaches, or to a robust polyhedral mesh generation tool for a novel polyhedral finite element approach. A polyhedral finite element code is explored, that retains most of the favorable properties of conventional finite element methods, while reducing the system size by up to an order of magnitude compared to conventional techniques for the same input surface.;In conjunction with a cardiac simulation code, the workflow is utilized to model finite-deformation cardiac mechanics. A quadratic tetrahedral mesh is generated from MRI data of the human heart ventricles. The constitutive law is comprised of an incompressible orthotropic hyperelastic stress response for the myocardium, plus an electrical activation-dependent active stress for the muscle fibers. Muscle fiber orientations are generated using a rule-based approach. Electrical activation times are read from a coupled electrophysiology code. A lumped circulatory model is used to impose time-dependent ventricular volume constraints. Simulation results are presented. The same mechanics are also implemented for the polyhedral finite element mesh, and preliminary verification results are presented.;The toolchain used in performing image-based cardiac mechanics simulations makes important improvements to the speed and robustness of image-based modeling techniques. As efforts continue to mature, so too does the promise for simulation to impact and improve healthcare.
机译:基于图像的建模和仿真已成为针对特定患者的医疗应用的重要分析和预测工具,包括大规模的计算机模拟患者研究,优化的医疗设备设计以及通过增材制造定制的手术指南和植入物。用于特定患者的建模和仿真的管道是:图像采集,图像分割,表面生成,网格生成,基于物理的建模和仿真以及临床应用。这项研究为这些步骤建立了一个半自动工作流程,其中包括一个新颖的基于图像的网格划分工具Shabaka。该工具链通过基于磁共振成像(MRI)数据对跳动的人的心脏进行建模来演示。Shabaka工作流程可确保可靠地执行管道的每个步骤。医学图像使用阈值化,区域增长和手动技术进行处理和分割。使用基于Voronoi的新颖算法从图像蒙版中提取水密表面网格。为了科学计算的目的,表面网格既可以提供给常规有限元方法的四面体网格划分程序,也可以提供给新颖的多面体有限元方法的鲁棒多面网格生成工具。探索了一种多面体有限元代码,该代码保留了传统有限元方法的大多数优势,同时与相同输入表面的传统技术相比,将系统大小减小了一个数量级。代码,工作流程用于建模有限变形心脏力学。根据人心室的MRI数据生成二次四面体网格。本构定律包括对心肌的不可压缩的正交各向异性超弹性应力响应,以及对肌纤维的依赖电激活的主动应力。使用基于规则的方法生成肌肉纤维的方向。从耦合的电生理代码读取电激活时间。集总循环模型用于施加时间依赖性的心室容量限制。给出了仿真结果。多面体有限元网格也实现了相同的机制,并给出了初步的验证结果。;用于执行基于图像的心脏力学模拟的工具链对基于图像的建模技术的速度和鲁棒性进行了重要的改进。随着努力的不断成熟,模拟技术有望影响和改善医疗保健的前景也越来越大。

著录项

  • 作者

    Hafez, Omar Mohamed.;

  • 作者单位

    University of California, Davis.;

  • 授予单位 University of California, Davis.;
  • 学科 Biomechanics.;Mechanical engineering.;Mechanics.
  • 学位 Ph.D.
  • 年度 2018
  • 页码 151 p.
  • 总页数 151
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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