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利用图像分析自动识别宫颈涂片中的二倍体参考细胞。

Automated identification of diploid reference cells in cervical smears using image analysis.

作者信息

van der Laak Jeroen A W M, Siebers Albertus G, Cuijpers Vincent M J I, Pahlplatz Martin M M, de Wilde Peter C M, Hanselaar Antonius G J M

机构信息

Department of Pathology, University Medical Center, Nijmegen, The Netherlands.

出版信息

Cytometry. 2002 Apr 1;47(4):256-64. doi: 10.1002/cyto.10078.

Abstract

BACKGROUND

Acquisition of DNA ploidy histograms by image analysis may yield important information regarding the behavior of premalignant cervical lesions. Accurate selection of nuclei for DNA measurement is an important prerequisite for obtaining reliable data. Traditionally, manual selection of nuclei of diagnostic and reference cells is performed by an experienced cytotechnologist. In the present study, a method for the fully automated identification of nuclei of diploid epithelial reference cells in Feulgen- restained Papanicolaou (PAP) smears is described.

METHODS

The automated procedure consists of a decision tree implemented on the measurement device, containing nodes with feature threshold values and multivariate discriminant functions. Nodes were constructed to recognize debris and inflammatory cells, as well as diploid and nondiploid epithelial cells of the uterine cervix. Evaluation of the classifier was performed by comparing resulting diploid integrated optical densities with those from manually selected reference cells.

RESULTS AND CONCLUSION

On average, automatically acquired values deviated 2.4% from manually acquired values, indicating that the method described in this paper may be useful in cytometric practice.

摘要

背景

通过图像分析获取DNA倍体直方图可能会产生有关宫颈前病变行为的重要信息。准确选择用于DNA测量的细胞核是获得可靠数据的重要前提。传统上,由经验丰富的细胞技术专家手动选择诊断细胞和参考细胞的细胞核。在本研究中,描述了一种在福尔根染色的巴氏(PAP)涂片中全自动识别二倍体上皮参考细胞核的方法。

方法

自动化程序由在测量设备上实现的决策树组成,包含具有特征阈值和多元判别函数的节点。构建节点以识别碎片和炎症细胞,以及子宫颈的二倍体和非二倍体上皮细胞。通过将所得二倍体积分光密度与手动选择的参考细胞的光密度进行比较来评估分类器。

结果与结论

自动获取的值平均比手动获取的值偏差2.4%,表明本文所述方法可能在细胞计数实践中有用。

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