基于图像的生物结构建模方法

Judy P. Yang
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引用次数: 5

摘要

摘要针对高分辨率医学图像,开发了一种基于图像的强形式微结构分析程序。考虑异质生物材料,如具有多孔成分的骨组织,相关的微观细胞问题和均质力学性能已经通过渐进均质化推导出来,以关联宏观尺度和微观尺度的层次。然而,对于几何高度不规则的生物图像,传统的基于网格的方法在模型重建过程中不可避免地会遇到网格依赖和网格失真等问题。利用水平集技术进行模型重建,可以有效地识别和分割具有复杂拓扑结构的生物组织图像,如实体骨架和骨材料中的孔隙。特别地,强形式搭配法的采用利用了点离散化的优势,构成了一个无缝的计算框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image-Based Procedure for Biostructure Modeling
AbstractFor high-resolution medical images, an image-based procedure is developed in strong form to perform microstructure analysis. Consider heterogeneous biomaterials such as bone tissue with porous composition—the associated microscopic cell problems and homogenized mechanical properties have been derived through the asymptotic homogenization to correlate the hierarchy in the macroscale and microscale. Nevertheless, for bioimages with highly irregular geometry, the process of model reconstruction by the traditional mesh-based methods unavoidably encounters issues such as mesh dependency and mesh distortion. Upon using the level set technique for model reconstruction, images of biological tissue showing complex topology can be identified and segmented into different phases effectively, such as the solid skeleton and pores in bone materials. In particular, the employment of the strong form collocation method takes advantage of point discretization and constitutes a seamlessly computational framework for ...
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