DocumentCode :
2437812
Title :
A neural network based integrated image processing environment for object recognition in medical applications
Author :
Ware, J.A. ; Ciuca, I.
Author_Institution :
Glamorgan Univ., UK
fYear :
1997
fDate :
11-13 Jun 1997
Firstpage :
149
Lastpage :
154
Abstract :
The paper outlines an integrated image processing environment that uses neural networks for object recognition and classification. The image processing environment which is Windows based, encapsulates a multiple-document interface (MDI) and is menu driven. Object (shape) parameter extraction is focused on features that are invariant in terms of translation, rotation and scale transformations. The neural network models incorporated into the environment allow both clustering and classification of objects from the analysed image. Mapping neural networks perform input sensitivity analysis on the extracted feature measurements and thus facilitates the removal of irrelevant features and improvements in the degree of generalisation
Keywords :
feature extraction; generalisation (artificial intelligence); image classification; image recognition; medical image processing; neural nets; object recognition; sensitivity analysis; Windows-based image processing environment; analysed image; extracted feature measurements; generalisation; input sensitivity analysis; irrelevant feature removal; mapping neural networks; medical applications; menu driven image processing environment; multiple-document interface; neural network based integrated image processing environment; object classification; object clustering; object parameter extraction; object recognition; rotation; scale transformations; translation; Biomedical imaging; Color; Feature extraction; Image edge detection; Image processing; Image segmentation; Intelligent networks; Neural networks; Object recognition; Pattern recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer-Based Medical Systems., 1997. Proceedings., Tenth IEEE Symposium on
Conference_Location :
Maribor
ISSN :
1063-7125
Print_ISBN :
0-8186-7928-X
Type :
conf
DOI :
10.1109/CBMS.1997.596425
Filename :
596425
Link To Document :
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