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子宫癌自动细胞筛查的基础研究。V. 用于改进CYBEST的数据分析。

Fundamental study of automatic cytoscreening for uterine cancer. V. Data analysis for imporvement of CYBEST.

作者信息

Tanaka N, Ikeda H, Ueno T, Watanabe S, Imasato Y, Kashida R

出版信息

Acta Cytol. 1977 Jul-Aug;21(4):536-8.

PMID:333841
Abstract

The particles selected by CYBEST as "abnormal cells" at the stage of coarse scanning were examined by direct microscopy to determine whether they were actural cells or not. Approximately 20 to 30 per cent of these were cell clusters and/or clumped leukocytes and red cell or specks of dust. Such incidents interfered considerably with a precise cytologic assessment. To eliminate this problem by means of a software algorithm, experiments were carried out setting thresholds for cell feature values. When the values obtained by machine measurement exceeded the theshold values the particles concerned were automatically disregarded, as interfering indidents, at the state of the coarse scanning. The approach was found to have substantial value in the operation of CYBEST as a pescreening device.

摘要

CYBEST在粗扫描阶段选择为“异常细胞”的颗粒,通过直接显微镜检查以确定它们是否为实际细胞。其中约20%至30%是细胞团簇和/或聚集的白细胞、红细胞或灰尘颗粒。此类情况极大地干扰了精确的细胞学评估。为通过软件算法消除此问题,进行了设定细胞特征值阈值的实验。当机器测量获得的值超过阈值时,相关颗粒在粗扫描阶段作为干扰因素被自动忽略。结果发现该方法在CYBEST作为初步筛查设备的操作中具有重要价值。

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