Automated detection of working area of peripheral blood smears using mathematical morphology.
Automated detection of working area of peripheral blood smears using mathematical morphology.
复制标题
使用数学形态自动检测外周血涂片的工作区域。
DOI：
10.1155/2003/642562
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发表时间：
2003
期刊：
影响因子：
--
通讯作者：
Flandrin G
中科院分区：
文献类型：
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作者：
Angulo J;Flandrin G
该论文提出了一种自动检测 May-Grünwuald Giemsa 染色的外周血涂片工作区域的技术。最佳区域定义为涂片分布良好的部分。当红细胞停止重叠（在体膜侧）时，该区域开始，并在红细胞开始失去其清晰的中心区域（在羽毛边缘侧）时结束。该方法可以在低放大倍数（浸没物镜×25或×16）下扫描的图像中快速检测该区域。该算法由两个阶段组成。首先，应用使用数学形态学的图像分析程序来提取红细胞、红细胞的中心和具有中心的红细胞。其次，计算三种粒子的连通分量的数量，并计算扩散系数ρs和重叠系数ρo。十四张涂片的数据说明了该技术的使用方式及其性能。彩色图可在 http://www.esacp.org/acp/2003/25‐1/angulo.htm 上查看。
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 on http://www.esacp.org/acp/2003/25‐1/angulo.htm.