Application of neural networks to the segmentation of MRI: comparison of different networks

S. Maleki; Mohammad Amin Zia; Ahmad R. Mirzai; F. Hariri

doi:10.1117/12.279551

30 October 1997 Application of neural networks to the segmentation of MRI: comparison of different networks

S. Maleki, Mohammad Amin Zia, Ahmad R. Mirzai, F. Hariri

Proceedings Volume 3164, Applications of Digital Image Processing XX; (1997) https://doi.org/10.1117/12.279551
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

In this paper a comparative study of the application of four neural networks for the segmentation of magnetic resonance images of brain, is proposed. The segmentation of MRI images enable one to present tissues of the same category with an equal gray level resulting in a more clear image for future diagnosis and treatments. Results of using three supervised networks, i.e. multi-layered perceptron, probabilistic neural network and radial basis functions and one unsupervised network, i.e. adaptive resonance theory 2 will be reported.

Citation Download Citation

S. Maleki, Mohammad Amin Zia, Ahmad R. Mirzai, and F. Hariri "Application of neural networks to the segmentation of MRI: comparison of different networks", Proc. SPIE 3164, Applications of Digital Image Processing XX, (30 October 1997); https://doi.org/10.1117/12.279551

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