FCM Clustering Algorithms for Segmentation of Brain MR Images
The study of brain disorders requires accurate tissue segmentation of magnetic resonance (MR) brain images which is very important for detecting tumors, edema, and necrotic tissues. Segmentation of brain images, especially into three main tissue types: Cerebrospinal Fluid (CSF), Gray Matter (GM), an...
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | Advances in Fuzzy Systems |
| Online Access: | http://dx.doi.org/10.1155/2016/3406406 |
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| _version_ | 1832565000930066432 |
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| author | Yogita K. Dubey Milind M. Mushrif |
| author_facet | Yogita K. Dubey Milind M. Mushrif |
| author_sort | Yogita K. Dubey |
| collection | DOAJ |
| description | The study of brain disorders requires accurate tissue segmentation of magnetic resonance (MR) brain images which is very important for detecting tumors, edema, and necrotic tissues. Segmentation of brain images, especially into three main tissue types: Cerebrospinal Fluid (CSF), Gray Matter (GM), and White Matter (WM), has important role in computer aided neurosurgery and diagnosis. Brain images mostly contain noise, intensity inhomogeneity, and weak boundaries. Therefore, accurate segmentation of brain images is still a challenging area of research. This paper presents a review of fuzzy c-means (FCM) clustering algorithms for the segmentation of brain MR images. The review covers the detailed analysis of FCM based algorithms with intensity inhomogeneity correction and noise robustness. Different methods for the modification of standard fuzzy objective function with updating of membership and cluster centroid are also discussed. |
| format | Article |
| id | doaj-art-0056c60616534901aabebfae40563f2e |
| institution | Kabale University |
| issn | 1687-7101 1687-711X |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Fuzzy Systems |
| spelling | doaj-art-0056c60616534901aabebfae40563f2e2025-02-03T01:09:31ZengWileyAdvances in Fuzzy Systems1687-71011687-711X2016-01-01201610.1155/2016/34064063406406FCM Clustering Algorithms for Segmentation of Brain MR ImagesYogita K. Dubey0Milind M. Mushrif1Department of Electronics and Telecommunication, Yeshwantrao Chavan College of Engineering, Wanadongri, Hingna Road, Nagpur, Maharashtra 441110, IndiaDepartment of Electronics and Telecommunication, Yeshwantrao Chavan College of Engineering, Wanadongri, Hingna Road, Nagpur, Maharashtra 441110, IndiaThe study of brain disorders requires accurate tissue segmentation of magnetic resonance (MR) brain images which is very important for detecting tumors, edema, and necrotic tissues. Segmentation of brain images, especially into three main tissue types: Cerebrospinal Fluid (CSF), Gray Matter (GM), and White Matter (WM), has important role in computer aided neurosurgery and diagnosis. Brain images mostly contain noise, intensity inhomogeneity, and weak boundaries. Therefore, accurate segmentation of brain images is still a challenging area of research. This paper presents a review of fuzzy c-means (FCM) clustering algorithms for the segmentation of brain MR images. The review covers the detailed analysis of FCM based algorithms with intensity inhomogeneity correction and noise robustness. Different methods for the modification of standard fuzzy objective function with updating of membership and cluster centroid are also discussed.http://dx.doi.org/10.1155/2016/3406406 |
| spellingShingle | Yogita K. Dubey Milind M. Mushrif FCM Clustering Algorithms for Segmentation of Brain MR Images Advances in Fuzzy Systems |
| title | FCM Clustering Algorithms for Segmentation of Brain MR Images |
| title_full | FCM Clustering Algorithms for Segmentation of Brain MR Images |
| title_fullStr | FCM Clustering Algorithms for Segmentation of Brain MR Images |
| title_full_unstemmed | FCM Clustering Algorithms for Segmentation of Brain MR Images |
| title_short | FCM Clustering Algorithms for Segmentation of Brain MR Images |
| title_sort | fcm clustering algorithms for segmentation of brain mr images |
| url | http://dx.doi.org/10.1155/2016/3406406 |
| work_keys_str_mv | AT yogitakdubey fcmclusteringalgorithmsforsegmentationofbrainmrimages AT milindmmushrif fcmclusteringalgorithmsforsegmentationofbrainmrimages |