Error permissibility of neural network used for renal corpuscle area enhancement.
- Author:
Jun ZHANG
1
;
Hong ZHU
;
Zhaohui XU
;
Gang LIANG
;
Ruirui JI
Author Information
1. School of Automation, Xi'an University of Technology, Xi'an 710048, China.
- Publication Type:Journal Article
- MeSH:
Humans;
Image Processing, Computer-Assisted;
Kidney Glomerulus;
pathology;
Neural Networks (Computer)
- From:
Journal of Biomedical Engineering
2006;23(3):653-656
- CountryChina
- Language:Chinese
-
Abstract:
In the automatic analysis system of the kidney-tissue image, boundary enhancement for glomerulus area is a vital step. Complex characteristics of kidney-tissue image leads to the difficulty in boundary features description. This paper suggests a kind of feature template under the special boundary definition. A nonlinear threshold surface is constructed by neural network, then the proper surface can be selected to enhance boundary with the influence of error permissibility being taken into account. Experimental results indicate that this learning method with error permissibility can enhance the boundary of glomerulus and suppress noises at the same time, so it can obtain good processed effects and have a fine performance highly adaptive to various sample images.
