Classification of MRI Images Using Particle Swarm Optimization Based Support Vector Machine for Tumor Detection
Keywords:
Magnetic resonance imaging (MRI), computed tomography, Image Segmentation, Region of Interest (ROI)Abstract
This paper searches the possibility of pertaining techniques for segmenting the regions of medical image. For this we require to examine the use of different techniques which helps for detection and classification of image regions. In the paper, a new method is proposed for tumor detection using morphological operations to address brain tumor from MRI images to be used as a tool in real time during surgeries a new method using particle swarm optimization technique to recognize and remove the limit of a brain tumor. Using abnormal images of a variety of brain tumors, this study shows that the proposed algorithm provides a robust technique in expressions of accuracy and computation time, making it appropriate for real-time processing. Results also show that this algorithm is proficient of producing one-pixel-width continuous edges with accurate positioning of particular region where tumor was detected.
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