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Medical Image Segmentation Based on a Hybrid Region-Based Active Contour Model
A novel hybrid region-based active contour model is presented to segment medical images with intensity inhomogeneity. The energy functional for the proposed model consists of three weighted terms: global term, local term, and regularization term. The total energy is incorporated into a level set for...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4083809/ https://www.ncbi.nlm.nih.gov/pubmed/25028593 http://dx.doi.org/10.1155/2014/890725 |
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author | Liu, Tingting Xu, Haiyong Jin, Wei Liu, Zhen Zhao, Yiming Tian, Wenzhe |
author_facet | Liu, Tingting Xu, Haiyong Jin, Wei Liu, Zhen Zhao, Yiming Tian, Wenzhe |
author_sort | Liu, Tingting |
collection | PubMed |
description | A novel hybrid region-based active contour model is presented to segment medical images with intensity inhomogeneity. The energy functional for the proposed model consists of three weighted terms: global term, local term, and regularization term. The total energy is incorporated into a level set formulation with a level set regularization term, from which a curve evolution equation is derived for energy minimization. Experiments on some synthetic and real images demonstrate that our model is more efficient compared with the localizing region-based active contours (LRBAC) method, proposed by Lankton, and more robust compared with the Chan-Vese (C-V) active contour model. |
format | Online Article Text |
id | pubmed-4083809 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-40838092014-07-15 Medical Image Segmentation Based on a Hybrid Region-Based Active Contour Model Liu, Tingting Xu, Haiyong Jin, Wei Liu, Zhen Zhao, Yiming Tian, Wenzhe Comput Math Methods Med Research Article A novel hybrid region-based active contour model is presented to segment medical images with intensity inhomogeneity. The energy functional for the proposed model consists of three weighted terms: global term, local term, and regularization term. The total energy is incorporated into a level set formulation with a level set regularization term, from which a curve evolution equation is derived for energy minimization. Experiments on some synthetic and real images demonstrate that our model is more efficient compared with the localizing region-based active contours (LRBAC) method, proposed by Lankton, and more robust compared with the Chan-Vese (C-V) active contour model. Hindawi Publishing Corporation 2014 2014-06-16 /pmc/articles/PMC4083809/ /pubmed/25028593 http://dx.doi.org/10.1155/2014/890725 Text en Copyright © 2014 Tingting Liu et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Liu, Tingting Xu, Haiyong Jin, Wei Liu, Zhen Zhao, Yiming Tian, Wenzhe Medical Image Segmentation Based on a Hybrid Region-Based Active Contour Model |
title | Medical Image Segmentation Based on a Hybrid Region-Based Active Contour Model |
title_full | Medical Image Segmentation Based on a Hybrid Region-Based Active Contour Model |
title_fullStr | Medical Image Segmentation Based on a Hybrid Region-Based Active Contour Model |
title_full_unstemmed | Medical Image Segmentation Based on a Hybrid Region-Based Active Contour Model |
title_short | Medical Image Segmentation Based on a Hybrid Region-Based Active Contour Model |
title_sort | medical image segmentation based on a hybrid region-based active contour model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4083809/ https://www.ncbi.nlm.nih.gov/pubmed/25028593 http://dx.doi.org/10.1155/2014/890725 |
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