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Active Contours Using Additive Local and Global Intensity Fitting Models for Intensity Inhomogeneous Image Segmentation
This paper introduces an improved region based active contour method with a level set formulation. The proposed energy functional integrates both local and global intensity fitting terms in an additive formulation. Local intensity fitting term influences local force to pull the contour and confine i...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5075425/ https://www.ncbi.nlm.nih.gov/pubmed/27800011 http://dx.doi.org/10.1155/2016/9675249 |
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author | Soomro, Shafiullah Akram, Farhan Kim, Jeong Heon Soomro, Toufique Ahmed Choi, Kwang Nam |
author_facet | Soomro, Shafiullah Akram, Farhan Kim, Jeong Heon Soomro, Toufique Ahmed Choi, Kwang Nam |
author_sort | Soomro, Shafiullah |
collection | PubMed |
description | This paper introduces an improved region based active contour method with a level set formulation. The proposed energy functional integrates both local and global intensity fitting terms in an additive formulation. Local intensity fitting term influences local force to pull the contour and confine it to object boundaries. In turn, the global intensity fitting term drives the movement of contour at a distance from the object boundaries. The global intensity term is based on the global division algorithm, which can better capture intensity information of an image than Chan-Vese (CV) model. Both local and global terms are mutually assimilated to construct an energy function based on a level set formulation to segment images with intensity inhomogeneity. Experimental results show that the proposed method performs better both qualitatively and quantitatively compared to other state-of-the-art-methods. |
format | Online Article Text |
id | pubmed-5075425 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-50754252016-10-31 Active Contours Using Additive Local and Global Intensity Fitting Models for Intensity Inhomogeneous Image Segmentation Soomro, Shafiullah Akram, Farhan Kim, Jeong Heon Soomro, Toufique Ahmed Choi, Kwang Nam Comput Math Methods Med Research Article This paper introduces an improved region based active contour method with a level set formulation. The proposed energy functional integrates both local and global intensity fitting terms in an additive formulation. Local intensity fitting term influences local force to pull the contour and confine it to object boundaries. In turn, the global intensity fitting term drives the movement of contour at a distance from the object boundaries. The global intensity term is based on the global division algorithm, which can better capture intensity information of an image than Chan-Vese (CV) model. Both local and global terms are mutually assimilated to construct an energy function based on a level set formulation to segment images with intensity inhomogeneity. Experimental results show that the proposed method performs better both qualitatively and quantitatively compared to other state-of-the-art-methods. Hindawi Publishing Corporation 2016 2016-10-09 /pmc/articles/PMC5075425/ /pubmed/27800011 http://dx.doi.org/10.1155/2016/9675249 Text en Copyright © 2016 Shafiullah Soomro et al. https://creativecommons.org/licenses/by/4.0/ 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 Soomro, Shafiullah Akram, Farhan Kim, Jeong Heon Soomro, Toufique Ahmed Choi, Kwang Nam Active Contours Using Additive Local and Global Intensity Fitting Models for Intensity Inhomogeneous Image Segmentation |
title | Active Contours Using Additive Local and Global Intensity Fitting Models for Intensity Inhomogeneous Image Segmentation |
title_full | Active Contours Using Additive Local and Global Intensity Fitting Models for Intensity Inhomogeneous Image Segmentation |
title_fullStr | Active Contours Using Additive Local and Global Intensity Fitting Models for Intensity Inhomogeneous Image Segmentation |
title_full_unstemmed | Active Contours Using Additive Local and Global Intensity Fitting Models for Intensity Inhomogeneous Image Segmentation |
title_short | Active Contours Using Additive Local and Global Intensity Fitting Models for Intensity Inhomogeneous Image Segmentation |
title_sort | active contours using additive local and global intensity fitting models for intensity inhomogeneous image segmentation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5075425/ https://www.ncbi.nlm.nih.gov/pubmed/27800011 http://dx.doi.org/10.1155/2016/9675249 |
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