DocumentCode :
1131915
Title :
A recurrent cooperative/competitive field for segmentation of magnetic resonance brain images
Author :
Worth, Andrew J. ; Lehar, Steve ; Kennedy, David N.
Author_Institution :
Dept. of Cognitive & Neural Syst., Boston Univ., MA, USA
Volume :
4
Issue :
2
fYear :
1992
fDate :
4/1/1992 12:00:00 AM
Firstpage :
156
Lastpage :
161
Abstract :
The gray-white decision network is introduced as an application of a recurrent cooperative/competitive network for segmentation of magnetic resonance (MR) brain images. The three-layer dynamical system relaxes into a solution where each pixel is labeled as either gray matter, white matter, or other matter by considering raw input intensity, edge information, and neighbor interactions. This network is presented as an example of applying a neurally inspired recurrent cooperative/competitive field (RCCF) to a problem with multiple conflicting constraints. Applications of the network and its phase plane analysis are presented
Keywords :
biomedical NMR; brain; computerised pattern recognition; computerised picture processing; medical computing; neural nets; edge information; gray matter; gray-white decision network; magnetic resonance brain images; neighbor interactions; neural nets; phase plane analysis; pixel; raw input intensity; recurrent cooperative/competitive network; three-layer dynamical system; white matter; Brain; Humans; Image analysis; Image segmentation; Labeling; Magnetic analysis; Magnetic resonance; Magnetic resonance imaging; Magnetic separation; Neuroscience;
fLanguage :
English
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1041-4347
Type :
jour
DOI :
10.1109/69.134252
Filename :
134252
Link To Document :
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