Automated classification of magnetic resonance brain images using Wavelet Genetic Algorithm and Support Vector Machine

2010 ◽  
Author(s):  
Ahmed Kharrat ◽  
Mohamed Ben Messaoud ◽  
Mohamed Abid ◽  
Karim Gasmi ◽  
Nacera Benamrane
Keyword(s):  
Genetic Algorithm ◽  
Support Vector Machine ◽  
Magnetic Resonance ◽  
Support Vector ◽  
Automated Classification ◽  
Brain Images

Fully automated classification of HARDI in vivo data using a support vector machine

NeuroImage ◽  
2009 ◽  
Vol 46 (3) ◽  
pp. 642-651 ◽  
Author(s):  
S. Schnell ◽  
D. Saur ◽  
B.W. Kreher ◽  
J. Hennig ◽  
H. Burkhardt ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Support Vector ◽  
Automated Classification

Medical Image Classification Using an Optimal Feature Extraction Algorithm and a Supervised Classifier Technique

2011 ◽  
Vol 3 (2) ◽  
pp. 19-33 ◽  
Author(s):  
Ahmed Kharrat ◽  
Karim Gasmi ◽  
Mohamed Ben Messaoud ◽  
Nacéra Benamrane ◽  
Mohamed Abid
Keyword(s):  
Genetic Algorithm ◽  
Support Vector Machine ◽  
Research Work ◽  
Reduction Rate ◽  
Support Vector ◽  
Forward Selection ◽  
Classification Rate ◽  
Brain Images ◽  
Input Module ◽  
Mr Brain Images

A new approach for automated diagnosis and classification of Magnetic Resonance (MR) human brain images is proposed. The proposed method uses Wavelets Transform (WT) as input module to Genetic Algorithm (GA) and Support Vector Machine (SVM). It segregates MR brain images into normal and abnormal. This contribution employs genetic algorithm for feature selection which requires much lighter computational burden in comparison with Sequential Floating Backward Selection (SFBS) and Sequential Floating Forward Selection (SFFS) methods. A percentage reduction rate of 88.63% is achieved. An excellent classification rate of 100% could be achieved using the support vector machine. The observed results are significantly better than the results reported in a previous research work employing Wavelet Transform and Support Vector Machine.

Sign in / Sign up

Export Citation Format

Share Document