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
Link To Document :
بازگشت