首页> 外文会议>International conference on medical image computing and computer-assisted intervention;MICCAI 2009 >High-Quality Model Generation for Finite Element Simulation of Tissue Deformation
【24h】

High-Quality Model Generation for Finite Element Simulation of Tissue Deformation

机译:用于组织变形有限元模拟的高质量模型生成

获取原文

摘要

In finite element simulation, size, shape, and placement of the elements in a model are significant factors that affect the interpolation and numerical errors of a solution. In medical simulations, such models are desired to have higher accuracy near features such as anatomical boundaries (surfaces) and they are often required to have element faces lying along these surfaces. Conventional modelling schemes consist of a segmentation step delineating the anatomy followed by a meshing step generating elements conforming to this segmentation. In this paper, a one-step energy-based model generation technique is proposed. An objective function is minimized when each element of a mesh covers similar image intensities while, at the same time, having desirable FEM characteristics. Such a mesh becomes essential for accurate models for deformation simulation, especially when the image intensities represent a mechanical feature of the tissue such as the elastic modulus. The use of the proposed mesh optimization is demonstrated on synthetic phantoms, 2D/3D brain MR images, and prostate ultrasound-elastography data.
机译:在有限元仿真中,模型中元素的大小,形状和位置是影响解决方案的插值和数值误差的重要因素。在医学模拟中,需要这样的模型在诸如解剖学边界(表面)之类的特征附近具有更高的精度,并且通常要求它们具有沿着这些表面放置的元素面。常规的建模方案包括描绘解剖结构的分割步骤,然后是生成符合该分割的元素的网格化步骤。本文提出了一种基于能量的单步模型生成技术。当网格的每个元素覆盖相似的图像强度,同时具有理想的FEM特性时,目标函数将最小化。这样的网格对于用于变形仿真的精确模型变得至关重要,尤其是当图像强度代表组织的机械特征(例如弹性模量)时。在合成体模,2D / 3D脑部MR图像和前列腺超声弹性成像数据上证明了所建议的网格优化的使用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号