DocumentCode :
3366313
Title :
Development of fuzzy neural tool for medical signal processing and imaging
Author :
Gan, W.S.
Author_Institution :
Acoustical Services Pte Ltd., Singapore
fYear :
1992
fDate :
14-17 Jun 1992
Firstpage :
633
Lastpage :
637
Abstract :
The author proposes the use of fuzzy neural networks to improve the resolution of medical images and the segmentation of medical images. The backpropagation neural network is used to obtain an optimized membership function. The author works out the algorithms to implement the fuzzy neural networks for both types of application. Preliminary results are given. An advantage of using fuzzy neural networks compared with conventional neural networks is the reduction of the number of elements in each neural network layer. Thus, computation time can be reduced. Another advantage of using neural networks is the solution of the ill-posed problem in the universe scattering problem such as the divergence problem
Keywords :
fuzzy control; image segmentation; medical image processing; neural nets; backpropagation neural network; fuzzy neural tool; medical images; medical signal processing; universe scattering problem; Backpropagation algorithms; Biomedical imaging; Biomedical signal processing; Fuzzy neural networks; Image resolution; Image segmentation; Neural networks; Scattering; Signal processing algorithms; Signal resolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer-Based Medical Systems, 1992. Proceedings., Fifth Annual IEEE Symposium on
Conference_Location :
Durham, NC
Print_ISBN :
0-8186-2742-5
Type :
conf
DOI :
10.1109/CBMS.1992.245028
Filename :
245028
Link To Document :
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