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...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 46; no. 11; pp. 1097 - 1113 |
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| Autores principales: | , , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Nov2008
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105574790&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105574790 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Nov2008 vid: 46 iid: 11 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 105574790 NLM19002516 2010101066 10.1007/s11517-008-0420-1 NLM19002516 105574790 ppf: 1097 ppct: 16 formats: fmt: @attributes: type: P tig: atl: An image-based modeling framework for patient-specific computational hemodynamics. aug: au: 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 affil: Biomedical Engineering Department, Mario Negri Institute for Pharmacological Research, Villa Camozzi, Ranica, BG, Italy sug: subj: Biophysics Image Processing, Computer Assisted Methods Models, Biological Aorta, Abdominal Physiology Cerebral Aneurysm Physiopathology Computer Simulation Phantoms, Imaging Software Human ab: 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. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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