Clustering Techniques on Brain MRI Naveen A.1, Velmurugan T.2 1Research Scholar Department of Computer Science, DG Vaishnav College, Arumbakkam, Chennai, Tamilnadu, India 2Professor, PG and Research Department of Computer Science, DG Vaishnav College, Arumbakkam, Chennai, Tamilnadu, India Online published on 16 March, 2018. Abstract In radiology Photostat of the human's anatomy and the corporeal parts on health and disease can be obtained by Magnetic resonance imaging technique. In the aspect of Brain, Segmentation is the technique in Magnetic Resonance Imaging, which is one of the effectual techniques, followed by many radiographers in discernment of any abnormality the brain attempts as well as the critical regions of the brain. these processes underpin with computerized and automated processing technique, so that analysis of the medical images made allay. the facet of segmentation technique is to obtain coherent analyze by obtaining the representation of images by pixels. The image segmentation using clustering technique helps in partition the different regions of the brain, white matter (WM), grey matter (GM), and cerebrospinal fluid spaces (CSF) into cluster or segments. These are the regions significant for physician and radiographers to detect, analyze and diagnose the abnormalities as well as the diseases. Adaptive Fuzzy K-means clustering algorithm proposes to differentiate those three regions, further the results are contrasted with that of fuzzy C-means clustering algorithm. the image segments from these outputs processes the solution in a qualitative approach proving that proposing method of algorithm is effectual for MRI brain images using segmentation techniques. This ensures accuracy. Based on Experimental evaluations, proposed algorithm reduces 0.721 ET (Execution Time) in seconds and enhances 2.03% SA (Segmentation Accuracy) of the proposed system compared than previous strategies. Top Keywords Segmentation technique, Magnetic Resonance Imaging (MRI), white matter (WM), grey matter (GM), cerebrospinal fluid spaces (CSF), Adaptive Fuzzy K-means (AFKM), fuzzy C-means clustering. Top |