Feature selection in order to extract multiple sclerosis lesions automatically in 3D brain MR images using combination of Support Vector Machine and Genetic algorithm

Hassan Khotanlou, Mahlagha Afrasiabi



This paper presents a new feature selection approach for automatically extracting   MS lesions in 3D MR images. Presented method is applicable to different types of Ms lesions. In this method, T1, T2 and FLAIR images are firstly preprocessed. In the next phase, effective features to extract MS lesions are selected by using a genetic algorithm. The fitness function of the genetic algorithm is the similarity index of a SVM classifier. The results obtained on different types of lesions have been evaluated by comparison with manual segmentations. This algorithm is evaluated on 15 real 3D MR images using several measures. As a result, the similarity index between MS regions determined by the proposed method and radiologists was %87 on average. Experiments and comparisons with other methods show the effectiveness and the efficiency of the proposed approach.


: Genetic algorithm, Medical images, classification, Support Vector Machine, MS lesions, Features selection

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