为了实现人体外周血白细胞的快速无重复自动扫描,提出了一种新的聚类方法——视窗聚类法。由于人体外周血白细胞在血液涂片中分布稀疏且不均匀,传统的利用高倍镜直接逐行扫描的人工方法效率比较低下。用高倍物镜有目的地对有白细胞的区域进行拍摄可以提高白细胞的扫描效率。用低倍物镜预扫描血片,由于低倍物镜视场大,在低倍图中,用图像处理的方法可获得白细胞核心坐标。视窗聚类方法首先用最大最小距离聚类方法确定白细胞核心原始聚类中心,再按照高倍镜视窗大小对聚类中心进行调整,在确保各聚类视窗内无重复白细胞存在的同时,尽可能合并原始聚类中心,减少总的聚类中心个数。以新的视窗聚类中心组成高倍物镜扫描路径扫描血片,可保证高倍图像最大程度地包含尽可能多的白细胞,进而减少高倍图像的拍摄次数,实现了白细胞的快速无重复扫描。实验表明,用该方法获取110个无重复的白细胞图像仅需要拍摄高倍图像72~85幅,整个过程大概需要1.5~2.0 min。同时,视窗聚类方法可以在无人监管的情况下完全避免白细胞图像的重复拍摄,实现了人体外周血白细胞的自动扫描。

A leukocyte image fast scanning method based on max-min distance clustering is proposed. Because of the lower proportion and uneven distribution of leukocytes in human peripheral blood, there will not be any leukocyte in lager quantity of the captured images if we directly scan the blood smear along an ordinary zigzag scanning routine with high power (100^x) objective. Due to the larger field of view of low power (10^x) objective, the captured low power blood smear images can be used to locate leukocytes. All of the located positions make up a specific routine, if we scan the blood smear along this routine with high power objective, there will be definitely leukocytes in almost all of the captured images. Considering the number of captured images is still large and some leukocytes may be redundantly captured twice or more, a leukocyte clustering method based on max–min distance clustering is developed to reduce the total number of captured images as well as the number of redundantly captured leukocytes. This method can improve the scanning efficiency obviously. The experimental results show that the proposed method can shorten scanning time from 8.0–14.0 min to 2.5–4.0 min while extracting 110 nonredundant individual high power leukocyte images.