Manuscript Number : CSEIT1722214

Brain Tumor Segmentation Using K-Means Clustering and Fuzzy C-Means Algorithms

Authors(2) :-K. Gayathri, D. Vasanthi

Tumor is an uncontrolled growth of tissue in any part of the body. The tumor is of different types and they have different characteristics and different treatment. Normally the anatomy of the brain can be viewed by the MRI scan or CT scan. MRI scanned image is used for the entire process. The MRI scan is more comfortable than any other scans for diagnosis. It will not affect the human body, because it doesn’t practice any radiation. It is centered on the magnetic field and radio waves. After the segmentation, which is done through k-means clustering and fuzzy c-means algorithms the brain tumor is detected and its exact location is identified.FCM with k-means clustering algorithms is used to increase the accuracy ratio of tumor detection system. The tumor area is calculated for accurate result.

Authors and Affiliations

K. Gayathri
Department of Electronics and Communication Engineering, IFET college of Engineering, Villupuram, Tamil Nadu, India
D. Vasanthi
Department of Electronics and Communication Engineering, IFET college of Engineering, Villupuram, Tamil Nadu, India

Magnetic Resonance Image (MRI), Fuzzy C Means Algorithm (FCM), K-Means Algorithm.

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Publication Details

Published in : Volume 2 | Issue 2 | March-April 2017
Date of Publication : 2017-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 704-707
Manuscript Number : CSEIT1722214
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

K. Gayathri, D. Vasanthi, "Brain Tumor Segmentation Using K-Means Clustering and Fuzzy C-Means Algorithms", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 2, pp.704-707, March-April-2017. |          | BibTeX | RIS | CSV

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