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

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

Oct 1997

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1997spie.3164..161m&link_type=abstract

Proc. SPIE Vol. 3164, p. 161-168, Applications of Digital Image Processing XX, Andrew G. Tescher; Ed.

Statistics

Applications

Scientific paper

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.

Affiliated with

Also associated with

No associations

Rating

Application of neural networks to the segmentation of MRI: comparison of different networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Application of neural networks to the segmentation of MRI: comparison of different networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Application of neural networks to the segmentation of MRI: comparison of different networks will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-1158846