Automated Detection of Working Area of Peripheral Blood Smears Using Mathematical Morphology

Abstract

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 ×25 or ×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 ρs and the coefficient of overlapping ρo are calculated. The data from fourteen smears illustrate how the technique is used and its performance. Colour figures can be viewed onhttp://www.esacp.org/acp/2003/25‐1/angulo.htm.