The Tumor Detection Neural Network using Texture Features

The Tumor Detection Neural Network using Texture Features
Authors : Mira Parmar, Mrs. Sadhana Pai
Publication Date: 03-08-2015


Author(s):  Mira Parmar, Mrs. Sadhana Pai

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:   Volume. 4 - Issue. 08 , August - 2015

e-ISSN:   2278-0181

 DOI:  http://dx.doi.org/10.17577/IJERTV4IS080084


Magnetic Resonance Imaging (MRI) is a medical imaging technique which provides information about the human tissue anatomy. The MRI images are high in tissue contrast which helps the radiologist to visualize the finer details of the most delicate parts of the body such as brain. Because of the variety of shapes, locations and image intensities within the MRI, it becomes the challenging task for the radiologists to diagnose the brain tumor correctly at its early stage. In this paper, a Tumor Detection Neural (TDN) network has been developed which detects whether the MRI for test is having benign or malignant tumor. First the tumor region is extracted using the image processing techniques which enhance the image and removes the skull region of the image. Then the texture features of the image are extracted using the Gray Level Co-occurrence Matrix (GLCM) with which the TDN network is trained. On basis of the training, the TDN network displays a message whether the test image is having a benign or malignant tumor.


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