Image analysis of nucleated red blood cells

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Abstract

Bone marrow smears stained with Giemsa were scanned with a video camera under computer control. Forty-two cells representing the six differentiation classes of the red bone marrow were sampled. Each cell was digitized into 70 × 70 pixels, each pixel representing a square area of 0.4 μm2 in the original image. The pixel gray values ranged between 0 and 255. Zero stood for white, 255 represented black, while the numbers in between stood for the various shades of gray. After separation and smoothing the images were processed with a Sobel operator outlining the points of steepest gray level change in the cell. These points constitute a closed curve denominated as inner cell boundary, separating the cell into an inner and an outer region. Two types of features were extraced from each cell: form features, e.g., area and length, and gray level features. Twenty-two features were tested for their discriminative merit. After selecting 16, the discriminant analysis program classified correctly all 42 cells into the 6 classes. © 1983.

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Zajicek, G., Shohat, M., Melnik, Y., & Yeger, A. (1983). Image analysis of nucleated red blood cells. Computers and Biomedical Research, 16(4), 347–356. https://doi.org/10.1016/0010-4809(83)90058-7

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