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Proceedings Paper

Support vector machine and morphological processing algorithm for red blood cell identification
Author(s): Lingtong Kong; Li Chang; Qingli Li; Mei Zhou; Hongying Liu; Fangmin Guo
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Paper Abstract

Hyperspectral imaging is an emerging imaging modality for medical applications. It provides more information than traditional optical image for owning two spatial dimensions and one spectral dimension. Multi dimension information of hyperspectral images can be used to classify different tissues and cells, while it’s difficult to distinguish them by traditional methods. The processing method presented in this paper is composed of two main blocks: Support Vector Machine (SVM) algorithm is adopted to identify different components of blood cells through the spectral dimension. In order to make it easy for blood cell counting, some morphological processing methods are used to process images through the spatial dimensions. This strategy, applying SVM and morphological processing methods, has been successfully tested for classifying objects among erythrocytes, leukocytes and serums in raw samples. Experimental results show that the proposed method is effective for red blood cells identification.

Paper Details

Date Published: 29 August 2016
PDF: 6 pages
Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100334P (29 August 2016); doi: 10.1117/12.2243725
Show Author Affiliations
Lingtong Kong, East China Normal Univ. (China)
Li Chang, East China Normal Univ. (China)
Qingli Li, East China Normal Univ. (China)
Mei Zhou, East China Normal Univ. (China)
Hongying Liu, East China Normal Univ. (China)
Fangmin Guo, East China Normal Univ. (China)


Published in SPIE Proceedings Vol. 10033:
Eighth International Conference on Digital Image Processing (ICDIP 2016)
Charles M. Falco; Xudong Jiang, Editor(s)

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