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《Computer Engineering and Applications》 2010-03
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A more effective algorithm of automatic recognition urinary sediment

ZHANG Can-long1,TANG Yan-ping2,WANG Qiang1,WEI Chun-rong3 1.College of Computer Science and Information Engineering,Guangxi Normal University,Guilin,Guangxi 541004,China 2.Department of Information Material Science and Engineering,Guilin University of Electronic Technology,Guilin,Guangxi 541004,China 3.College of Physics and Electronic Engineering,Guangxi Normal University,Guilin,Guangxi 541004,China  
An algorithm based on Support Vector Machine(SVM) and template matching is designed to classify the urinary sediment.Firstly,visible compositions in urinary sediment are classified roughly into big object and small object following their area,the former includes epithelial cells and pipe type,the latter includes crystallization,leukocyte and erythrocyte.Secondly,the template matching method is used to identify the crystallization,and by constructing an optimal SVM classifier,leukocyte and erythrocyte are different in the most extent.Finally,these big objects are classified into epithelial cells and pipe type following narrow extent.Experiment shows that the proposed method not only can gain better recognition rate(96.7%),but also reduces 22.4% computing time.
【Fund】: 广西省教育厅资助科研项目 No.200508107;; 广西师范大学青年基金(No.师政科技[2006]5号)~~
【CateGory Index】: TP391.41
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