Research Article

Selective Brain MRI Image Segmentation using Fuzzy C Mean Clustering Algorithm for Tumor Detection

by  Jesmon G. Paul, Tarun Kumar Rawat, Josna Job
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 144 - Issue 7
Published: Jun 2016
Authors: Jesmon G. Paul, Tarun Kumar Rawat, Josna Job
10.5120/ijca2016910455
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Jesmon G. Paul, Tarun Kumar Rawat, Josna Job . Selective Brain MRI Image Segmentation using Fuzzy C Mean Clustering Algorithm for Tumor Detection. International Journal of Computer Applications. 144, 7 (Jun 2016), 28-31. DOI=10.5120/ijca2016910455 

                        @article{ 10.5120/ijca2016910455,
                        author  = { Jesmon G. Paul,Tarun Kumar Rawat,Josna Job },
                        title   = { Selective Brain MRI Image Segmentation using Fuzzy C Mean Clustering Algorithm for Tumor Detection },
                        journal = { International Journal of Computer Applications },
                        year    = { 2016 },
                        volume  = { 144 },
                        number  = { 7 },
                        pages   = { 28-31 },
                        doi     = { 10.5120/ijca2016910455 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2016
                        %A Jesmon G. Paul
                        %A Tarun Kumar Rawat
                        %A Josna Job
                        %T Selective Brain MRI Image Segmentation using Fuzzy C Mean Clustering Algorithm for Tumor Detection%T 
                        %J International Journal of Computer Applications
                        %V 144
                        %N 7
                        %P 28-31
                        %R 10.5120/ijca2016910455
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

Brain MRI (Magnetic Resonance Imaging)[1] images are used to diagnose any abnormality associated with human brain by the physicians. But these images are often corrupted with noise which makes it difficult to diagnose any abnormality in initial stage of defect. Image processing techniques like image segmentation is used to extract important information out of noisy MRI images. But image segmentation process will also remove original minute details available in original image apart from noise because entire image will be clustered into few segments of same pixel intensity. In this paper a selective brain MRI image segmentation is proposed based on Fuzzy C Mean (FCM) Clustering algorithm [2] with image pixel weightage to retain necessary original image details intact.

References
  • RR Edelman, S Warach - New England Journal of Medicine, 1993 - Mass Medical Soc.
  • JC Bezdek, R Ehrlich, W Full - Computers & Geosciences, 1984 - Elsevier.
  • MS Mahaley Jr, C Mettlin, N Natarajan… - Journal of Neurosurgery, 1989 - thejns.org
  • Astrocytes induce blood–brain barrier properties in endothelial cells, RC Janzer, MC Raff - Nature, 1987 - nature.com
  • A Study of Computer-Assisted Tomography: I. The Incidence of Positive CAT Scans in an Asymptomatic Group of Patients. SW Wiesel, N Tsourmas, HL FEFFER, CM CITRIN… - Spine, 1984 - journals.lww.com
  • Tissue characterization with T1, T2, and proton density values: results in 160 patients with brain tumors. M Just, M Thelen - Radiology, 1988 - pubs.rsna.org.
  • Distance regularized level set evolution and its application to image segmentation. C Li, C Xu, C Gui, MD Fox - Image Processing, IEEE …, 2010 - ieeexplore.ieee.org
  • Data clustering: 50 years beyond K-means, AK Jain - Pattern recognition letters, 2010 – Elsevier
  • Edge detection in digital images using fuzzy logic technique AA Alshennawy, AA Aly - World Academy of Science, Engineering and Technology, International Journal of Computer, Electrical, Automation, Control and Information Engineering Vol:3, No:3, 2009
  • Optimizing of fuzzy c-means clustering algorithm using GA, M Alata, M Molhim, A Ramini - Update, 2008 - waset.org
  • Interpretation of the Correlation Coefficient: A Basic Review, Richard Taylor, EdD, RDCS, Cardiac Laboratory, Logan General Hospital, Logan, WV 25601.
  • Particle swarm optimization,J Kennedy - Encyclopedia of machine learning, 2011 - Springer
Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

K-Mean membership matrix Cluster center Objective function.

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