Share Email Print

Proceedings Paper

Application of neural networks to the segmentation of MRI: comparison of different networks
Author(s): S. Maleki; Mohammad Amin Zia; Ahmad R. Mirzai; F. Hariri
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper 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.

Paper Details

Date Published: 30 October 1997
PDF: 8 pages
Proc. SPIE 3164, Applications of Digital Image Processing XX, (30 October 1997); doi: 10.1117/12.279551
Show Author Affiliations
S. Maleki, Iran Azad Univ. (Iran)
Mohammad Amin Zia, Institute for Studies in Theoretical Physics and Mathematics (Iran)
Ahmad R. Mirzai, Iran Univ. of Science and Technology (Iran)
F. Hariri, Iran Univ. of Science and Technology (Iran)

Published in SPIE Proceedings Vol. 3164:
Applications of Digital Image Processing XX
Andrew G. Tescher, Editor(s)

© SPIE. Terms of Use
Back to Top