Nacéra Benamrane

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We purpose a hybrid approach for classification of brain tissues in magnetic resonance images (MRI) based on genetic algorithm (GA) and support vector machine (SVM). A wavelet based texture feature set is derived. The optimal texture features are extracted from normal and tumor regions by using spatial gray level dependence method (SGLDM). These features(More)
In this paper we propose a new approach for automated diagnosis and classification of Magnetic Resonance (MR) human brain images, using Wavelets Transform (WT) as input to Genetic Algorithm (GA) and Support Vector Machine (SVM). The proposed method segregates MR brain images into normal and abnormal. Our contribution employs genetic algorithm for feature(More)
— The selection of features has a considerable impact on the success or failure of classification process. Feature selection refers to the procedure of selecting a subset of informative attributes to build models describing data. The main purpose of feature selection is to reduce the number of features used in classification while maintaining high(More)
With nearly 100.000 cases in Algeria, Alzheimer's disease (AD) represents a major public health problem. Therefore, several different automated methods have been developed to assist clinicians in their diagnosis. We propose here a method based on binary support vector machines (SVM) to distinguish between patients with Alzheimer disease (AD), patients with(More)
In this paper, we propose an approach based on the RBF neural networks and the genetic algorithms for magnetic resonance (MR) brain images segmentation. In the feature extraction stage, nine features are calculated and used as RBF network inputs. The genetic algorithm build automatically a RBF NN (It determines the number of hidden neurons, and their(More)
This paper presents an original approach for detecting and tracking of objects in medical image sequence. We propose a multi-agent system (MAS) based on NetLogo platform for implementing parametric contour active model or snake. In NetLogo, mobile agents (turtles) move over a grid of stationary agents (patches). In our proposed MAS, each mobile agent(More)