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ImageParser: a tool for finite element generation from three-dimensional medical images
BACKGROUND: The finite element method (FEM) is a powerful mathematical tool to simulate and visualize the mechanical deformation of tissues and organs during medical examinations or interventions. It is yet a challenge to build up an FEM mesh directly from a volumetric image partially because the re...
Autores principales: | , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2004
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC524181/ https://www.ncbi.nlm.nih.gov/pubmed/15461787 http://dx.doi.org/10.1186/1475-925X-3-31 |
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author | Yin, HM Sun, LZ Wang, G Yamada, T Wang, J Vannier, MW |
author_facet | Yin, HM Sun, LZ Wang, G Yamada, T Wang, J Vannier, MW |
author_sort | Yin, HM |
collection | PubMed |
description | BACKGROUND: The finite element method (FEM) is a powerful mathematical tool to simulate and visualize the mechanical deformation of tissues and organs during medical examinations or interventions. It is yet a challenge to build up an FEM mesh directly from a volumetric image partially because the regions (or structures) of interest (ROIs) may be irregular and fuzzy. METHODS: A software package, ImageParser, is developed to generate an FEM mesh from 3-D tomographic medical images. This software uses a semi-automatic method to detect ROIs from the context of image including neighboring tissues and organs, completes segmentation of different tissues, and meshes the organ into elements. RESULTS: The ImageParser is shown to build up an FEM model for simulating the mechanical responses of the breast based on 3-D CT images. The breast is compressed by two plate paddles under an overall displacement as large as 20% of the initial distance between the paddles. The strain and tangential Young's modulus distributions are specified for the biomechanical analysis of breast tissues. CONCLUSION: The ImageParser can successfully exact the geometry of ROIs from a complex medical image and generate the FEM mesh with customer-defined segmentation information. |
format | Text |
id | pubmed-524181 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2004 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-5241812004-10-24 ImageParser: a tool for finite element generation from three-dimensional medical images Yin, HM Sun, LZ Wang, G Yamada, T Wang, J Vannier, MW Biomed Eng Online Research BACKGROUND: The finite element method (FEM) is a powerful mathematical tool to simulate and visualize the mechanical deformation of tissues and organs during medical examinations or interventions. It is yet a challenge to build up an FEM mesh directly from a volumetric image partially because the regions (or structures) of interest (ROIs) may be irregular and fuzzy. METHODS: A software package, ImageParser, is developed to generate an FEM mesh from 3-D tomographic medical images. This software uses a semi-automatic method to detect ROIs from the context of image including neighboring tissues and organs, completes segmentation of different tissues, and meshes the organ into elements. RESULTS: The ImageParser is shown to build up an FEM model for simulating the mechanical responses of the breast based on 3-D CT images. The breast is compressed by two plate paddles under an overall displacement as large as 20% of the initial distance between the paddles. The strain and tangential Young's modulus distributions are specified for the biomechanical analysis of breast tissues. CONCLUSION: The ImageParser can successfully exact the geometry of ROIs from a complex medical image and generate the FEM mesh with customer-defined segmentation information. BioMed Central 2004-10-01 /pmc/articles/PMC524181/ /pubmed/15461787 http://dx.doi.org/10.1186/1475-925X-3-31 Text en Copyright © 2004 Yin et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open-access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Yin, HM Sun, LZ Wang, G Yamada, T Wang, J Vannier, MW ImageParser: a tool for finite element generation from three-dimensional medical images |
title | ImageParser: a tool for finite element generation from three-dimensional medical images |
title_full | ImageParser: a tool for finite element generation from three-dimensional medical images |
title_fullStr | ImageParser: a tool for finite element generation from three-dimensional medical images |
title_full_unstemmed | ImageParser: a tool for finite element generation from three-dimensional medical images |
title_short | ImageParser: a tool for finite element generation from three-dimensional medical images |
title_sort | imageparser: a tool for finite element generation from three-dimensional medical images |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC524181/ https://www.ncbi.nlm.nih.gov/pubmed/15461787 http://dx.doi.org/10.1186/1475-925X-3-31 |
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