DocumentCode
3252387
Title
Application of fuzzy neural networks to medical image processing
Author
Gan, W.S.
Author_Institution
Acoustical Services Pte Ltd., Singapore
Volume
4
fYear
1992
fDate
7-11 Jun 1992
Firstpage
386
Abstract
The author proposes the use of fuzzy neural networks to improve the resolution and segmentation of medical images. The backpropagation neural network is used to obtain an optimized membership function. The algorithms are presented to implement the fuzzy neural networks for both types of applications. Preliminary results are given. The advantage of using fuzzy neural networks compared with conventional neural networks is to reduce the number of elements in each neural network layer. Thus computation time can be reduced. Only tomographic images are considered
Keywords
computerised tomography; feedforward neural nets; fuzzy logic; image reconstruction; medical image processing; backpropagation neural network; fuzzy neural networks; fuzzy reasoning; ill-posed problems; inverse scattering; medical image processing; membership function; tomographic images; Biomedical image processing; Biomedical imaging; Computer networks; Fuzzy control; Fuzzy neural networks; Image restoration; Image segmentation; Neural networks; Nuclear magnetic resonance; X-ray tomography;
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.1992.227314
Filename
227314
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