Review on Automatic Brain Tumor Detection based on Gabor Wavelet

Review on Automatic Brain Tumor Detection based on Gabor Wavelet
Authors : Mr. Akshay M. Malviya, Prof. Atul S. Joshi
Publication Date: 03-01-2014


Author(s):  Mr. Akshay M. Malviya, Prof. Atul S. Joshi

Published in:   International Journal of Engineering Research & Technology

License:  This work is licensed under a Creative Commons Attribution 4.0 International License.

Website: www.ijert.org

Volume/Issue:   Vol. 3 - Issue 1 (January - 2014)

e-ISSN:   2278-0181


Medical image analysis is an important bio-medical application, these image analysis techniques are often used to detect abnormalities in human bodies through scan image Magnetic resonance (MR) images are a very useful tool to detect the tumor growth in brain but precise brain image segmentation is a difficult and time consuming process. In this paper we propose a method for automatic brain tumor diagnostic system from MR images. The system consists of three stages to detect and segment a brain tumor. In the first stage, MR image of brain is acquired and preprocessing is done to remove the noise and to sharpen the image. In the second stage, edges are detected by using gabor filter. In the third stage, threshold segmentation is done on the sharpened image to segment the brain tumor and the segmented image is post processed by morphological operations and tumor masking in order to remove the false segmented pixels. experiments show that technique accurately identifies and segments the brain tumor in MR images.


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