DocumentCode
1588026
Title
Cellular Neural Network Based Urinary Image Segmentation
Author
Zhang, Zanchao ; Xia, Shunren ; Duan, Huilong
Author_Institution
Zhejiang Univ., Hangzhou
Volume
2
fYear
2007
Firstpage
285
Lastpage
289
Abstract
A novel approach for urinary image segmentation based on cellular neural network (CNN) was presented in this paper. Before the image segmentation, a preprocessing by stretching the difference between every pixel and the local gray mean value for eliminating the disequilibrium of illumination and enhancing the edges of objects is considered here. The experiment results with more than 100 clinical urinary images show that this approach provides more accurate objects detection compared with conventional threshold based ones.
Keywords
cellular neural nets; image segmentation; medical image processing; object detection; cellular neural network; illumination disequilibrium; local gray mean value; objects detection; urinary image segmentation; Cellular neural networks; Diseases; Histograms; Image edge detection; Image segmentation; Lighting; Microscopy; Morphology; Pixel; Sediments; Urinary microscopic image; cellular neural network (CNN); distance transform; grayaverage-; object enhancement; segmentation;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location
Haikou
Print_ISBN
978-0-7695-2875-5
Type
conf
DOI
10.1109/ICNC.2007.294
Filename
4344361
Link To Document