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