Detection of Brain Tumor using Expectation Maximization (EM) and Watershed

A.C. Motagi¹ , V.S. Malemath²

1. Dept. Of Computer Science, KLE Dr. M.S. Sheshgiri College of Engineering, VTU, Belgaum, India.
2. Dept. Of Computer Science, KLE Dr. M.S. Sheshgiri College of Engineering, VTU, Belgaum, India.

Section:Research Paper, Product Type: Isroset-Journal
Vol.6 , Issue.3 , pp.76-80, Jun-2018

CrossRef-DOI:   https://doi.org/10.26438/ijsrcse/v6i3.7680

Online published on Jun 30, 2018

Copyright © A.C. Motagi, V.S. Malemath . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Human Body is made up of several cells which have their own capabilities. When these cells unrequitedly divide themselves, it develops into Tumor. The exact cause behind the loss of control over division is not known so far. Further growth of tumor would hinder the usual working of the brain. Hence detecting it in the first stage is necessary. It is a tedious task to accurately find the tumor. In case of Brain Tumor detection, there are several imaging techniques but MRI stands out with promising results. The proposed paper is motivated by the need for high precision when it comes to a human life. It considers MRI of brain and performs filtering, segmentation using Expectation Maximization and Watershed and also morphological operations. Later the results obtained from both the methods are combined to give a final image highlighting the tumor. Also, the accuracy of detecting the tumor is measured with the help of available truth images of MRI used.

Key-Words / Index Term :
MRI, Brain Tumor, Segmentation, Morphological Operations

References :
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