DocumentCode :
285321
Title :
A probabilistic neural network based image segmentation network for magnetic resonance images
Author :
Morrison, Matthew ; Attikiouzel, Y.
Author_Institution :
Centre for Intelligent Inf. Process. Syst., Univ. of Western Australia, Nedlands, WA, Australia
Volume :
3
fYear :
1992
fDate :
7-11 Jun 1992
Firstpage :
60
Abstract :
A network structure for segmenting magnetic resonance medical images is proposed. The incorporation of a probabilistic neural network structure into the segmentation process allows decisions regarding the characterization of each pixel to be made in a probabilistic manner, thus reducing the effect of an incorrect decision early in the process on the final segmentation result. The probabilistic neural network facilitates the generation of likelihood estimates for use in an iterative segmentation process, which was shown to produce good segmentation results on real magnetic resonance images
Keywords :
biomedical NMR; image segmentation; medical image processing; neural nets; probability; image segmentation network; iterative segmentation; likelihood estimate generation; magnetic resonance images; pixel characterization; probabilistic neural network; High-resolution imaging; Image analysis; Image segmentation; Intelligent systems; Iterative algorithms; Magnetic resonance; Magnetic resonance imaging; Muscles; Neural networks; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
Type :
conf
DOI :
10.1109/IJCNN.1992.227189
Filename :
227189
Link To Document :
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