Support Vector Machine for MRI Stroke Classfication
Journal Title: International Journal on Computer Science and Engineering - Year 2014, Vol 6, Issue 4
Abstract
Magnetic resonance imaging (MRI) is a low-risk, non-invasive imaging technique without ionizing radiation hazard, providing high quality/high contrast images and functional images of anatomical structures and organs. In this study, a method to classify the MRI images of the brain related to stroke is presented. Stroke is a sudden development of neurological damage. In this paper, the MRI images for stroke classification use Gabor filters and Histograms to extract features from the images. In the proposed feature extraction method, the features from Gabor filter and histogram features are fused. The extracted features are classified using Support Vector Machine (SVM) with various kernels. Experimental results are shown that the presented method achieves satisfactory classification accuracy
Authors and Affiliations
A. S. Shanthi , M. Karthikeyan
Keywords
Related Articles
- EP ID EP126680
- DOI -
- Views 118
- Downloads 0
A Genetic Algorithm Approach for the Solution of Economic Load Dispatch Problem
This paper presents the application of Genetic algorithm (GA) to solve the economic load dispatch problem of the power system. The effectiveness of the proposed algorithm has been demonstrated on two different test syste...
IMPROVED SOFTWARE QUALITY ASSURANCE TECHNIQUES USING SAFE GROWTH MODEL
In our lives are governed by large, complex systems with ncreasingly complex software, and the safety, security, and reliability of these systems has become a major concern. As the software in today’s systems grows larg...
A generic conceptual and UML model for the multi-echelon distribution supply chain
The Multi-Echelon Distribution Supply Chain (MEDSC) is a multifaceted structure, focusing on the integration of all factors that involved in the overall distribution process of finished products to the customers. The gro...
A Study of Image Segmentation and Edge Detection Techniques
Image segmentation is the key behind image understanding. Image segmentation is one of the most important steps leading to the analysis of processed image data. It is the prime area of research in computer vision. A numb...
Intelligent Farm Expert Multi Agent System
Farming data has been rapidly increasing in volume in different Web data sources. Querying multiple data sources manually on the internet is time consuming and laborious process for farmers. Traditional information syste...