A weighted region-based level set method for image segmentation with intensity inhomogeneity.

Image segmentation is a fundamental task in image processing and is still a challenging problem when processing images with high noise, low resolution and intensity inhomogeneity. In this paper, a weighted region-based level set method, which is based on the techniques of local statistical theory, l...

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Autores principales:	Haiping Yu, Ping Sun, Fazhi He, Zhihua Hu
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/63986a7912d6480195e952e9eda650de
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id	oai:doaj.org-article:63986a7912d6480195e952e9eda650de
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spelling	oai:doaj.org-article:63986a7912d6480195e952e9eda650de2021-12-02T20:17:45ZA weighted region-based level set method for image segmentation with intensity inhomogeneity.1932-620310.1371/journal.pone.0255948https://doaj.org/article/63986a7912d6480195e952e9eda650de2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0255948https://doaj.org/toc/1932-6203Image segmentation is a fundamental task in image processing and is still a challenging problem when processing images with high noise, low resolution and intensity inhomogeneity. In this paper, a weighted region-based level set method, which is based on the techniques of local statistical theory, level set theory and curve evolution, is proposed. Specifically, a new weighted pressure force function (WPF) is first presented to flexibly drive the closed contour to shrink or expand outside and inside of the object. Second, a faster and smoother regularization term is added to ensure the stability of the curve evolution and that there is no need for initialization in curve evolution. Third, the WPF is integrated into the region-based level set framework to accelerate the speed of the curve evolution and improve the accuracy of image segmentation. Experimental results on medical and natural images demonstrate that the proposed segmentation model is more efficient and robust to noise than other state-of-the-art models.Haiping YuPing SunFazhi HeZhihua HuPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 8, p e0255948 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Haiping Yu Ping Sun Fazhi He Zhihua Hu A weighted region-based level set method for image segmentation with intensity inhomogeneity.
description	Image segmentation is a fundamental task in image processing and is still a challenging problem when processing images with high noise, low resolution and intensity inhomogeneity. In this paper, a weighted region-based level set method, which is based on the techniques of local statistical theory, level set theory and curve evolution, is proposed. Specifically, a new weighted pressure force function (WPF) is first presented to flexibly drive the closed contour to shrink or expand outside and inside of the object. Second, a faster and smoother regularization term is added to ensure the stability of the curve evolution and that there is no need for initialization in curve evolution. Third, the WPF is integrated into the region-based level set framework to accelerate the speed of the curve evolution and improve the accuracy of image segmentation. Experimental results on medical and natural images demonstrate that the proposed segmentation model is more efficient and robust to noise than other state-of-the-art models.
format	article
author	Haiping Yu Ping Sun Fazhi He Zhihua Hu
author_facet	Haiping Yu Ping Sun Fazhi He Zhihua Hu
author_sort	Haiping Yu
title	A weighted region-based level set method for image segmentation with intensity inhomogeneity.
title_short	A weighted region-based level set method for image segmentation with intensity inhomogeneity.
title_full	A weighted region-based level set method for image segmentation with intensity inhomogeneity.
title_fullStr	A weighted region-based level set method for image segmentation with intensity inhomogeneity.
title_full_unstemmed	A weighted region-based level set method for image segmentation with intensity inhomogeneity.
title_sort	weighted region-based level set method for image segmentation with intensity inhomogeneity.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/63986a7912d6480195e952e9eda650de
work_keys_str_mv	AT haipingyu aweightedregionbasedlevelsetmethodforimagesegmentationwithintensityinhomogeneity AT pingsun aweightedregionbasedlevelsetmethodforimagesegmentationwithintensityinhomogeneity AT fazhihe aweightedregionbasedlevelsetmethodforimagesegmentationwithintensityinhomogeneity AT zhihuahu aweightedregionbasedlevelsetmethodforimagesegmentationwithintensityinhomogeneity AT haipingyu weightedregionbasedlevelsetmethodforimagesegmentationwithintensityinhomogeneity AT pingsun weightedregionbasedlevelsetmethodforimagesegmentationwithintensityinhomogeneity AT fazhihe weightedregionbasedlevelsetmethodforimagesegmentationwithintensityinhomogeneity AT zhihuahu weightedregionbasedlevelsetmethodforimagesegmentationwithintensityinhomogeneity
_version_	1718374347013357568

A weighted region-based level set method for image segmentation with intensity inhomogeneity.

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