MR image classification by the neural network and the genetic algorithms

Author

Olmez, Tamer ; Dokur, Zumray ; Yazgan, Ertugrul

Author_Institution

Electr.-Electron. Fac., Istanbul Tech. Univ., Turkey

Volume

3

fYear

1996

fDate

31 Oct-3 Nov 1996

Firstpage

1140

Abstract

A novel neural network trained by the genetic algorithms (GAs) is presented. Each neuron of the network forms a closed region in an input space. The locations of the centers of the closed regions (CR) are optimized in order to minimize the number of the neurons used and to improve the classification performance. After the network is trained by the set which is formed by the supervisor, it is used to classify a magnetic resonance (MR) image with a tumor

Keywords

biomedical NMR; genetic algorithms; image classification; medical image processing; neural nets; MR image classification; centers locations; classification performance improvement; closed region; genetic algorithm-trained neural net; input space; magnetic resonance imaging; medical diagnostic imaging; neurons used number minimization; tumor; Chromium; Engineering in Medicine and Biology Society; Genetic algorithms; Genetic mutations; Image classification; Magnetic heads; Magnetic resonance; Neoplasms; Neural networks; Neurons;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1996. Bridging Disciplines for Biomedicine. Proceedings of the 18th Annual International Conference of the IEEE

Conference_Location

Amsterdam

Print_ISBN

0-7803-3811-1

Type

conf

DOI

10.1109/IEMBS.1996.652745

Filename

652745