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Segmentation of Multiple Sclerosis Lesions in Brain MR Images Using Spatially Constrained Possibilistic Fuzzy C-Means Classification
This paper introduces a novel methodology for the segmentation of brain MS lesions in MRI volumes using a new clustering algorithm named SCPFCM. SCPFCM uses membership, typicality and spatial information to cluster each voxel. The proposed method relies on an initial segmentation of MS lesions in T1...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Medknow Publications & Media Pvt Ltd
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3347225/ https://www.ncbi.nlm.nih.gov/pubmed/22606670 |
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author | Khotanlou, Hassan Afrasiabi, Mahlagha |
author_facet | Khotanlou, Hassan Afrasiabi, Mahlagha |
author_sort | Khotanlou, Hassan |
collection | PubMed |
description | This paper introduces a novel methodology for the segmentation of brain MS lesions in MRI volumes using a new clustering algorithm named SCPFCM. SCPFCM uses membership, typicality and spatial information to cluster each voxel. The proposed method relies on an initial segmentation of MS lesions in T1-w and T2-w images by applying SCPFCM algorithm, and the T1 image is then used as a mask and is compared with T2 image. The proposed method was applied to 10 clinical MRI datasets. The results obtained on different types of lesions have been evaluated by comparison with manual segmentations. |
format | Online Article Text |
id | pubmed-3347225 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Medknow Publications & Media Pvt Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-33472252012-05-09 Segmentation of Multiple Sclerosis Lesions in Brain MR Images Using Spatially Constrained Possibilistic Fuzzy C-Means Classification Khotanlou, Hassan Afrasiabi, Mahlagha J Med Signals Sens Original Article This paper introduces a novel methodology for the segmentation of brain MS lesions in MRI volumes using a new clustering algorithm named SCPFCM. SCPFCM uses membership, typicality and spatial information to cluster each voxel. The proposed method relies on an initial segmentation of MS lesions in T1-w and T2-w images by applying SCPFCM algorithm, and the T1 image is then used as a mask and is compared with T2 image. The proposed method was applied to 10 clinical MRI datasets. The results obtained on different types of lesions have been evaluated by comparison with manual segmentations. Medknow Publications & Media Pvt Ltd 2011 /pmc/articles/PMC3347225/ /pubmed/22606670 Text en Copyright: © Journal of Medical Signals and Sensors http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Khotanlou, Hassan Afrasiabi, Mahlagha Segmentation of Multiple Sclerosis Lesions in Brain MR Images Using Spatially Constrained Possibilistic Fuzzy C-Means Classification |
title | Segmentation of Multiple Sclerosis Lesions in Brain MR Images Using Spatially Constrained Possibilistic Fuzzy C-Means Classification |
title_full | Segmentation of Multiple Sclerosis Lesions in Brain MR Images Using Spatially Constrained Possibilistic Fuzzy C-Means Classification |
title_fullStr | Segmentation of Multiple Sclerosis Lesions in Brain MR Images Using Spatially Constrained Possibilistic Fuzzy C-Means Classification |
title_full_unstemmed | Segmentation of Multiple Sclerosis Lesions in Brain MR Images Using Spatially Constrained Possibilistic Fuzzy C-Means Classification |
title_short | Segmentation of Multiple Sclerosis Lesions in Brain MR Images Using Spatially Constrained Possibilistic Fuzzy C-Means Classification |
title_sort | segmentation of multiple sclerosis lesions in brain mr images using spatially constrained possibilistic fuzzy c-means classification |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3347225/ https://www.ncbi.nlm.nih.gov/pubmed/22606670 |
work_keys_str_mv | AT khotanlouhassan segmentationofmultiplesclerosislesionsinbrainmrimagesusingspatiallyconstrainedpossibilisticfuzzycmeansclassification AT afrasiabimahlagha segmentationofmultiplesclerosislesionsinbrainmrimagesusingspatiallyconstrainedpossibilisticfuzzycmeansclassification |