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Brain Tumor Detection from Pre-Processed MR Images Using Segmentation Techniques

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2nd National Conference on Computing, Communication and Sensor Network
© 2011 by IJCA Journal
Number 2 - Article 1
Year of Publication: 2011
Authors:
Sarbani Datta
Dr. Monisha Chakraborty

Sarbani Datta and Dr. Monisha Chakraborty. Brain Tumor Detection from Pre-Processed MR Images using Segmentation Techniques. IJCA Special Issue on 2nd National Conference- Computing, Communication and Sensor Network (CCSN) (2):1-5, 2011. Published by Foundation of Computer Science, New York, USA. BibTeX

@article{key:article,
	author = {Sarbani Datta and Dr. Monisha Chakraborty},
	title = {Brain Tumor Detection from Pre-Processed MR Images using Segmentation Techniques},
	journal = {IJCA Special Issue on 2nd National Conference- Computing, Communication and Sensor Network (CCSN)},
	year = {2011},
	number = {2},
	pages = {1-5},
	note = {Published by Foundation of Computer Science, New York, USA}
}

Abstract

Magnetic resonance imaging (MRI) has become a common way to study brain tumor. In this paper we pre-process the two-dimensional magnetic resonance images of brain and subsequently detect the tumor using edge detection technique and color based segmentation algorithm. Edge-based segmentation has been implemented using operators e.g. Sobel, Prewitt, Canny and Laplacian of Gaussian operators. The color-based segmentation method has been accomplished using K-means clustering algorithm. The color-based segmentation carefully selects the tumor from the pre-processed image as a clustering feature. The present work demonstrates that the method can successfully detect the brain tumor and thereby help the doctors for analyzing tumor size and region. The algorithms have been developed on MATLAB version 7.6.0 (R2008a) platform.

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