In this paper, a new method Based on Fuzzy Hopfield Neural Network for segmentation of MRI Brain images is proposed. In MRI Images, the Noise of imaging process can cause error in the conventional intensity base classification methods. In our algorithm, by optimizing the energy function Fuzzy Hopfield Neural network, we considered the effect of the neighbors of a pixel in classification of that pixel, and therefore we modify the structure of this network against the effect of noise problem. In other word in our method the labeling pixel has been influenced by the labels in the immediate neighborhoods. The results obtained from the proposed algorithm show that this method has an acceptable accuracy for segmentation of the brain's images. © 2006 Research Publishing Services.
CITATION STYLE
Rezai-Rad, G., & Ebrahimi, R. V. (2006). Modified fuzzy hopfield neural network using for MRI image segmentation. In ICBPE 2006 - Proceedings of the 2006 International Conference on Biomedical and Pharmaceutical Engineering (pp. 58–61). https://doi.org/10.1109/ICBPE.2006.348554
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