11 February 2011 Study of cell classification with a diffraction imaging flow cytometer method
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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.
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Ke Dong, Kenneth M. Jacobs, Yu Sa, Yuanming Feng, Jun Q. Lu, Xin-Hua Hu, "Study of cell classification with a diffraction imaging flow cytometer method", Proc. SPIE 7902, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues IX, 790215 (11 February 2011); doi: 10.1117/12.875096; https://doi.org/10.1117/12.875096

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