Cellular Neural Network Based Urinary Image Segmentation

Authors:
Zanchao Zhang;Shunren Xia;Huilong Duan
Affiliations:
Zhejiang University, China;Zhejiang University, China;Zhejiang University, China
Venue:
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 02
Year:
2007

Citing 0
Cited 2

Multilevel image segmentation with adaptive image context based thresholding

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A New Method Based on Adaptive Discrete Wavelet Entropy Energy and Neural Network Classifier (ADWEENN) for Recognition of Urine Cells from Microscopic Images Independent of Rotation and Scaling

Journal of Medical Systems

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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.