Title :
Cellular Neural Network Based Urinary Image Segmentation
Author :
Zhang, Zanchao ; Xia, Shunren ; Duan, Huilong
Author_Institution :
Zhejiang Univ., Hangzhou
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;
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
DOI :
10.1109/ICNC.2007.294