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Detection of Tumor in Mammographic Images by RBF Neural Network and Multi Population Genetic Algorithm

Belgrana Fatima Zohra, Benamrane Nacéra Published in Signal Processing

International Journal of Applied Information Systems
Year of Publication: 2013
© 2012 by IJAIS Journal
10.5120/ijais12-450669
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  1. Belgrana Fatima Zohra and Benamrane Nacera. Article: Detection of Tumor in Mammographic Images by RBF Neural Network and Multi Population Genetic Algorithm. International Journal of Applied Information Systems 6(3):1-5, October 2013. BibTeX

    @article{key:article,
    	author = "Belgrana Fatima Zohra and Benamrane Nacera",
    	title = "Article: Detection of Tumor in Mammographic Images by RBF Neural Network and Multi Population Genetic Algorithm",
    	journal = "International Journal of Applied Information Systems",
    	year = 2013,
    	volume = 6,
    	number = 3,
    	pages = "1-5",
    	month = "October",
    	note = "Published by Foundation of Computer Science, New York, USA"
    }
    

Abstract

In this paper, we propose an approach for detection of anomalies present in medical images. The idea is to combine tow metaphors: Neural Networks (NN) and Evolutionary Algorithm (EA) in a hybrid system. The Radial Basis Function Neural Network (RBF NN) and Multi Population Genetic Algorithm (MPGA) are coupled in one system called neural-evolutionary algorithm. After applying the growing region algorithm to extract regions, the RBF NN detects the suspect regions. Some of experimental results on mammographic images show the feasibility of the proposed approach.

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Keywords

Tumor Detection, Interpretation, RBF NN, MPGA Mammographic Images