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Blood cell image segmentation on color and GVF Snake for Leukocyte classification on SVM
KTH.
2012 (English)In: Guangxue Jingmi Gongcheng/Optics and Precision Engineering, ISSN 1004-924X, Vol. 20, no 12, 2781-2790 p.Article in journal (Refereed) Published
Abstract [en]

A leukocyte classification method was proposed by using image technologies.Firstly, based on image color information, image distance transformation and the Snake of Gradient Vector Flow (GVF Snake), the leukocytes were extracted in a blood cell image, and then the high saturation trait of the leukocyte nuclei was combined the morphological mathematics and GVF Snake to detect the nuclei in the leukocyte image. According to the features of morphometry, color and texture for cells, the Support Vector Machines (SVMs) were taken to classify the leukocytes. The results show that the proposed image segmentation method and the classifier to classify the leukocytes can achieve the accuracy by 89.6%. Compared to other traditional cell image segmentation and analysis methods, the proposed method is satisfactory.

Place, publisher, year, edition, pages
2012. Vol. 20, no 12, 2781-2790 p.
Keyword [en]
Blood cell image, Gradient Vector Flow(GVF) Snake, Image classification, Image extraction, Leukocyte classification, Support Vector Machine(SVM)
National Category
Medical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-116855DOI: 10.3788/OPE.20122012.2781Scopus ID: 2-s2.0-84872133466OAI: oai:DiVA.org:kth-116855DiVA: diva2:601150
Note

QC 20130128

Available from: 2013-01-28 Created: 2013-01-28 Last updated: 2016-11-24Bibliographically approved

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