Use of nuclear morphometry characteristics to distinguish between normal and abnormal cervical glandular histologies.

Richard Swartz, Loyd West, Iouri Boiko, Anais Malpica, Calum MacAulay, Anita Carraro, Martial Guillaud, Dennis Cox, Michele Follen
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引用次数: 12

Abstract

This is a methodological study exploring the use of quantitative histopathology applied to the cervix to discriminate between normal and cancerous (consisting of adenocarcinoma and adenocarcinoma in situ) tissue samples. The goal is classifying tissue samples, which are populations of cells, from measurements on the cells. Our method uses one particular feature, the IODs-Index, to create a tissue level feature. The specific goal of this study is to find a threshold for the IODs-Index that is used to create the tissue level feature. The main statistical tool is Receiver Operating Characteristic (ROC) curve analysis. When applied to the data, our method achieved promising results with good estimated sensitivity and specificity for our data set. The optimal threshold for the IODs-Index was found to be 2.12.

使用核形态计量学特征来区分正常和异常的宫颈腺体组织。
这是一项方法学研究,探索应用于子宫颈的定量组织病理学来区分正常和癌(包括腺癌和原位腺癌)组织样本。目标是通过对细胞的测量对组织样本(即细胞群)进行分类。我们的方法使用一个特定的特征,即ids - index,来创建一个组织级别的特征。本研究的具体目标是找到用于创建组织水平特征的IODs-Index的阈值。主要的统计工具是受试者工作特征(ROC)曲线分析。当应用于数据时,我们的方法取得了很好的结果,对我们的数据集具有良好的估计灵敏度和特异性。结果表明,该指标的最佳阈值为2.12。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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