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Anatomically Based Geometric Modelling Using Medical Image Data: Methods and Programs
The human organs geometric modeling software which can achieve two-dimensional medical image browsing, pretreatment and three dimensional (3D) reconstruction in this paper is designed. This software implements medical image segmentation using the method combining the region growing and the interacti...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Bentham Open
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4468590/ https://www.ncbi.nlm.nih.gov/pubmed/26089991 http://dx.doi.org/10.2174/1874120701509010126 |
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author | Wang, Monan Sun, Lei Liu, Yuming |
author_facet | Wang, Monan Sun, Lei Liu, Yuming |
author_sort | Wang, Monan |
collection | PubMed |
description | The human organs geometric modeling software which can achieve two-dimensional medical image browsing, pretreatment and three dimensional (3D) reconstruction in this paper is designed. This software implements medical image segmentation using the method combining the region growing and the interactive segmentation. Also, the MC surface reconstruction algorithm is utilized to achieve the three-dimensional reconstruction. Furthermore, the software is projected by Visual C++. And then, to legitimately express the structural information of skeleton and muscle, the software is employed to obtain the geometric model using the segmentation and three-dimensional reconstruction for data of skeleton and muscle medical images of the object of study. |
format | Online Article Text |
id | pubmed-4468590 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Bentham Open |
record_format | MEDLINE/PubMed |
spelling | pubmed-44685902015-06-18 Anatomically Based Geometric Modelling Using Medical Image Data: Methods and Programs Wang, Monan Sun, Lei Liu, Yuming Open Biomed Eng J Article The human organs geometric modeling software which can achieve two-dimensional medical image browsing, pretreatment and three dimensional (3D) reconstruction in this paper is designed. This software implements medical image segmentation using the method combining the region growing and the interactive segmentation. Also, the MC surface reconstruction algorithm is utilized to achieve the three-dimensional reconstruction. Furthermore, the software is projected by Visual C++. And then, to legitimately express the structural information of skeleton and muscle, the software is employed to obtain the geometric model using the segmentation and three-dimensional reconstruction for data of skeleton and muscle medical images of the object of study. Bentham Open 2015-06-09 /pmc/articles/PMC4468590/ /pubmed/26089991 http://dx.doi.org/10.2174/1874120701509010126 Text en © Wang et al.; Licensee Bentham Open. http://creativecommons.org/licenses/by-nc/3.0/ This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited. |
spellingShingle | Article Wang, Monan Sun, Lei Liu, Yuming Anatomically Based Geometric Modelling Using Medical Image Data: Methods and Programs |
title | Anatomically Based Geometric Modelling Using Medical Image Data: Methods and Programs |
title_full | Anatomically Based Geometric Modelling Using Medical Image Data: Methods and Programs |
title_fullStr | Anatomically Based Geometric Modelling Using Medical Image Data: Methods and Programs |
title_full_unstemmed | Anatomically Based Geometric Modelling Using Medical Image Data: Methods and Programs |
title_short | Anatomically Based Geometric Modelling Using Medical Image Data: Methods and Programs |
title_sort | anatomically based geometric modelling using medical image data: methods and programs |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4468590/ https://www.ncbi.nlm.nih.gov/pubmed/26089991 http://dx.doi.org/10.2174/1874120701509010126 |
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