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Automated Detection of Working Area of Peripheral Blood Smears Using Mathematical Morphology
Author(s) -
Jesús Angulo,
Georges Flandrin
Publication year - 2002
Publication title -
analytical cellular pathology
Language(s) - English
Resource type - Journals
eISSN - 2210-7185
pISSN - 2210-7177
DOI - 10.1155/2003/642562
Subject(s) - blood smear , peripheral blood , mathematical morphology , enhanced data rates for gsm evolution , computer science , giemsa stain , edge detection , image (mathematics) , pattern recognition (psychology) , artificial intelligence , materials science , computer vision , image processing , optics , physics , biology , pathology , medicine , malaria , immunology
The paper presents a technique to automatically detect the working area of peripheral blood smears stained with May-Grünwuald Giemsa. The optimal area is defined as the well spread part of the smear. This zone starts when the erythrocytes stop overlapping (on the body film side) and finishes when the erythrocytes start losing their clear central zone (on the feather edge side). The approach yields a quick detection of this area in images scanned under low magnifying power (immersion objective x 25 or x 16). The algorithm consists of two stages. First, an image analysis procedure using mathematical morphology is applied for extracting the erythrocytes, the centers of erythrocytes and the erythrocytes with center. Second, the number of connected components from the three kinds of particles is counted and the coefficient of spreading rho(s) and the coefficient of overlapping rho(o) are calculated. The data from fourteen smears illustrate how the technique is used and its performance. Colour figures can be viewed on http://www.esacp.org/acp/2003/25-1/angulo.htm.

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