Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
This study presents a system has the ability to detect and classify brain cancer effectively and efficiently based-on processing images that are combined with a Magnetic Resonance Imaging (MRI) technique. MRI has high features in dealing with human life such as safety, reliability and it is ability to image in any plane. The proposed system starts with the preprocessing of images includes resizing and enhancement of gray images of brain tumor. Textures features of the brain tumor are extracted using two algorithms called GCLM and k-means. The final stage to classify the tumor if benign or malign was accomplished using two techniques are k-Nearest Neighbor algorithm (kNN) and Support Vector Machine (SVM). The simulation results using MATLAB environment, showed that the accuracy of SVM classifier was better than kNN in the classification of brain tumor where the results are 79 and 73%, respectively. But the value of specificity of the system for kNN method was higher than SVM and the results are 87.5 and 61%, respectively.
How to cite this article:
Hassan Jassim Motlak. MRI Technique Based Detection and Classification of Brain Tumor using
Support Vector Machine (SVM) and k-Nearest Neighbor (kNN).
DOI: https://doi.org/10.36478/jeasci.2019.3625.3629
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2019.3625.3629