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Microscopic Image Analysis and Recognition on Pathological Cells

YIN Cong1,LUAN Qiuping1,FENG Nianlun2(1.Shandong College of Electronic Technology,Jinan 250014,China;2.Shandong Provincial Hospital,Jinan 250021,China)  
According to the features of the configuration and color information on the pathological cells,an adaptive automatic threshold segmentation based on the RGB and HIS color spaces was presented,which was available to segment suspected cancer cells and nucleus from the complex backgrounds in the microscopic images.The edges of the suspected cells and nucleus were detected by using Canny operator.Using the technology of eight chain codes tracking,the feature values of suspected cells were extracted.The transcendental features and calculating formulas were presented to recognize the suspected cells.Meanwhile,by comparing the natural cells and suspected cells,the detection method was decided.The results show that the proposed algorithm can efficiently segment cell images and receive higher accuracy of cell diagnosis.
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