CONTEXT INFORMATION IN AUTOMATED CERVICAL SMEAR ANALYSIS

这项研究的长期目标是开发和测试自动化 细胞图像分析在宫颈癌诊断和预后评估中的应用 癌我们以前的研究表明，语境分析（低 场景的分辨率分析）和标记分析（形态测量变化 在“正常”外观的细胞中）将重要信息添加到高 乳腺、前列腺和宫颈的分辨率单个细胞分析 肿瘤形成 以前的研究分几个步骤进行， 效率很低，只允许我们收集小数据集。 拟议研究的主要目标是开发一种 综合分析系统（IAS）将采用更先进的 结合单细胞分析、背景分析和标记分析的联合收割机方法。 的 本研究的第一个目的是开发一个系统，允许同时 单层细胞的背景、标志物和单个细胞分析 宫颈脱落细胞的制备。 这将包括使用 适应性方法，包括先验信息， 分析过程。 第二个目的是检验组合方法论 以确定它是否比任何单一分析提供了改进 法第三个目的是应用这些技术来调查 区分持续/渐进与倒退的可行性， 负面案例 这项研究应能对控制成本产生重大影响， 提供子宫颈细胞学检查作子宫颈癌预先检查 自动化细胞学可以部分弥补合格的 细胞技术专家 它还可以提供更客观的标准， 各级经验的宫颈癌的诊断和预后 和培训及其有效 同样的方法最终可以应用于专家 诊断和教学系统。 此外，在这方面取得的进展 研究应易于转移到其他类型的人类癌症。 因此，我们预计这项研究将对 癌症预防和控制的实际和科学方面。

The long-term objective of this research is to develop and test automated cell image analysis for the improved diagnosis and prognosis of cervical cancer. our previous research has shown that contextual analysis (low resolution analysis of scenes) and marker analysis (morphometric changes in "normal" looking cells) adds significant information to high resolution individual cell analysis of breast, prostate, and cervical neoplasia. The previous studies were performed in several steps, which was inefficient and only permitted us to collect small data sets. The primary objective of the proposed research is to develop an Integrated Analysis System (IAS) that will employ more sophisticated methods to combine the single cell, contextual, and marker analyses. The first aim of this research is to develop a system to permit simultaneous contextual, marker, and individual cell analyses of monolayer preparations of exfoliated cervical cells. This will include the use of adaptive methodologies that incorporate a priori information to guide the analysis process. The second aim is to test the combined methodolology to determine whether it provides an improvement over any single analysis method. The third aim is to apply these technique to investigate the feasibility of discriminating persistent/progressive from regressive and negative cases. This research should have significant impact on cost-containment and availability of cervical cytology for pre-screening of cervical cancer Automated cytology can partly offset the growing shortage of qualified cytotechnologists. It can also provide more objective criteria for diagnosis and prognosis of cervical neoplasia at all levels of experience and training. The same methodology can eventually be applied to expert systems for diagnosis and teaching. Moreover, advances made in this research should be readily transferable to other types of human cancer. Thus, we expect that this research will have far-reaching effects on practical as well as scientific aspects of cancer prevention and control.