Real-Valued Negative Selection (RNS) for MR Brain Image Classification

Luiz Otávio V.B. Oliveira and Isabela N. Drummond


Negative selection, Image classification, Artificial immune system, Genetic algorithm


This work presents a technique based on artificial immune system (AIS) for MR brain image classification. The method is an approach based on real-valued negative selection (RNS) algorithm and the use of a genetic algorithm to find a good combination of the input parameters in the classifier. The tests were carried out on synthetic MR brain images containing multiple sclerosis lesions. Preliminary results obtained shows that our approach is promising. Our implementation is developed in Java using the Weka environment.

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