<article_id>JIC_V1_N3_RP3</article_id>
<title>Segmentation Of Brain MRI Images For Tumor Detection By Optimizing C-Means Clustering Method</title>
<author>Kailash Sinha</author>
<author>G.R. Sinha</author>
<journal>Journal on Instrumentation & Control Engineering</journal>
<issn>2321 – 1148</issn>
<volume>1</volume>
<issue>3</issue>
<first_page>14</first_page>
<last_page>21</last_page>
<keywords>MRI, Brain Tumor, Segmentation, C-Means Clustering, Genetic Algorithm</keywords>
<abstract>Magnetic Resonance Imaging (MRI) is one of the best technologies currently being used for diagnosing brain tumor. Tumor detection and segmentation from MRI image is very important in medical imaging but apart from time taken in diagnosis accuracy of detection is also poor. For segmentation of medical images, clustering techniques such as kmeans and c-means clustering methods are widely used. The authors have implemented c-means clustering method and optimized its performance by using genetics algorithm. The combined approach resulted in improvement of segmentation efficiency and higher value of true positive pixels belonging to tumor region.</abstract>
<date>May - July 2013</date>
<copyright>Copyright &copy; 2013 i-manager publications. All rights reserved.</copyright>
<publisher>i-manager Publications</publisher>
<article_url>http://www.imanagerpublications.com/Article.aspx?ArticleId=2352</article_url>