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

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 a...

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Detalles Bibliográficos
Publicado en:Medical & Biological Engineering & Computing Vol. 46; no. 11; pp. 1097 - 1113
Autores principales: Antiga L, Piccinelli M, Botti L, Ene-Iordache B, Remuzzi A, Steinman DA, Antiga, Luca, Piccinelli, Marina, Botti, Lorenzo, Ene-Iordache, Bogdan, Remuzzi, Andrea, Steinman, David A
Formato: research Journal Article
Publicado: Springer Nature Nov2008
Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario: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.