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Proceedings Paper

Study of cell classification with a diffraction imaging flow cytometer method
Author(s): Ke Dong; Kenneth M. Jacobs; Yu Sa; Yuanming Feng; Jun Q. Lu; Xin-Hua Hu
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Paper Abstract

With a diffraction imaging flow cytometer, we have acquired and analyzed the diffraction imaging data from 5 types of cultured cells. A gray level co-occurrence matrix (GLCM) algorithm was applied to extract the interference fringe related textures from the diffraction image data. Six GLCM parameters were chosen and imported into a support vector machine algorithm for automated classification of about 20 cells for each of the 5 cell types. We found that the GLCM based algorithm has the capacity for rapid processing of diffraction images and yield feature parameters for subsequent cell classification except the T- and B-lymphocytes.

Paper Details

Date Published: 11 February 2011
PDF: 6 pages
Proc. SPIE 7902, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues IX, 790215 (11 February 2011); doi: 10.1117/12.875096
Show Author Affiliations
Ke Dong, TEO Systems, Inc. (United States)
Kenneth M. Jacobs, East Carolina Univ. (United States)
Yu Sa, Tianjin Univ. (China)
Yuanming Feng, Tianjin Univ. (China)
Jun Q. Lu, East Carolina Univ. (United States)
Xin-Hua Hu, TEO Systems, Inc. (United States)
East Carolina Univ. (United States)

Published in SPIE Proceedings Vol. 7902:
Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues IX
Daniel L. Farkas; Dan V. Nicolau; Robert C. Leif, Editor(s)

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