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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/77959


    Title: Blood Cell Image Classification Based on Hierarchical SVM
    Authors: 胡若梅;Hu, Rouh-Mei;蕭震緯;Hsiao, Chen-Wei;陳榮銘;Chen, Rong-Ming;蔡進發;Jeffrey, J.P.Tsai
    Contributors: 生物與醫學資訊學系
    Date: 2011.12
    Issue Date: 2013-12-26 17:35:34 (UTC+8)
    Abstract: The problem of identifying and counting blood cells within the blood smear is of both theoretical and practical interest. The differential counting of blood cells provides invaluable information to pathologist for diagnosis and treatment of many diseases. In this paper we propose an efficient hierarchical blood cell image identification and classification method based on multi-class support vector machine. In this automated process, segmentation and classification of blood cells are the most important stages. We segment the stained blood cells in digital microscopic images and extract the geometric features for each segment to identify and classify the different types of blood cells. The experimental results are compared with the manual results obtained by the pathologist, and demonstrate the effectiveness of the proposed method.
    Relation: 2011 IEEE International Symposium on Multimedia
    Appears in Collections:[生物資訊與醫學工程學系 ] 會議論文

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