A SURVEY OF FUZZY C-MEANS BASED ALGORITHMS FOR SEGMENTATION OF BRAIN MAGNETIC RESONANCE IMAGES

Abstract-Brain tissue segmentation aims to segment different tissues such as white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) from magnetic resonance images (MRI). In the past, many researchers have proposed MRI segmentation techniques in the field of medical image and soft computi...

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Bibliographic Details
Published inInternational journal of advanced research in computer science Vol. 9; no. 1; pp. 282 - 284
Main Author Nazir, Nighat
Format Journal Article
LanguageEnglish
Published Udaipur International Journal of Advanced Research in Computer Science 20.02.2018
Subjects
Algorithms
Brain
Cerebrospinal fluid
Image segmentation
Magnetic resonance imaging
Medical research
Soft computing
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ISSN0976-5697
0976-5697
DOI10.26483/ijarcs.v9i1.5264

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Summary:Abstract-Brain tissue segmentation aims to segment different tissues such as white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) from magnetic resonance images (MRI). In the past, many researchers have proposed MRI segmentation techniques in the field of medical image and soft computing. A number of segmentation techniques have been proposed among them thresholding, region-based segmentation, classification-based segmentation are the mostly used technique. In this paper, a comprehensive overview of fuzzy C-means (FCM) based algorithms for MRI segmentation is presented.
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ISSN:0976-5697
0976-5697
DOI:10.26483/ijarcs.v9i1.5264