An image-based modeling framework for patient-specific computational hemodynamics

被引:0
作者
Luca Antiga
Marina Piccinelli
Lorenzo Botti
Bogdan Ene-Iordache
Andrea Remuzzi
David A. Steinman
机构
[1] Mario Negri Institute for Pharmacological Research,Biomedical Engineering Department
[2] University of Bergamo,Industrial Engineering Department
[3] University of Toronto,Biomedical Simulation Laboratory, Department of Mechanical and Industrial Engineering
来源
Medical & Biological Engineering & Computing | 2008年 / 46卷
关键词
Patient-specific modeling; Image segmentation; Computational geometry; Mesh generation; CFD; Hemodynamics;
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学科分类号
摘要
We present a modeling framework designed for patient-specific computational hemodynamics to be performed in the context of large-scale studies. The framework takes advantage of the integration of image processing, geometric analysis and mesh generation techniques, with an accent on full automation and high-level interaction. Image segmentation is performed using implicit deformable models taking advantage of a novel approach for selective initialization of vascular branches, as well as of a strategy for the segmentation of small vessels. A robust definition of centerlines provides objective geometric criteria for the automation of surface editing and mesh generation. The framework is available as part of an open-source effort, the Vascular Modeling Toolkit, a first step towards the sharing of tools and data which will be necessary for computational hemodynamics to play a role in evidence-based medicine.
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