CONTEXT INFORMATION IN AUTOMATED CERVICAL SMEAR ANALYSIS

自动宫颈涂片分析中的背景信息

• 批准号: 3185091
• 负责人: DAVID J ZAHNISER
• 金额: $ 21.62万
• 依托单位: TUFTS MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 1987
• 资助国家: 美国
• 起止时间: 1987-06-01 至 1990-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3185091
• 关键词: artificial intelligence; biomedical automation; computer assisted diagnosis; computer data analysis; cytodiagnosis; cytology; diagnosis design /evaluation; diagnosis quality /standard; diagnostic tests; human subject; image processing; mass screening; neoplasm /cancer diagnosis; single cell analysis

The overall aim of this project is to improve automated cervical smear image analysis techniques sufficiently to: 1) routinely provide additional diagnostic information to supplement that provided by human visual examination, and 2) provide accurate, cost effective prescreening capabilities. By furnishing additional quantitative diagnostic information, such automated systems would permit the practicing cytopathologist to make more accurate and refined diagnostic judgements, which would lead to improved patient management. By providing a practical prescreening capability, such systems would increase the efficiency and efficacy of health care delivery. Current automated cervical smear analysis research employs only the analysis of isolated cells, and practical automated analysis is not yet a reality. The primary contribution of this project will be the completion of development and testing of image analysis techniques that extract information from cells and other objects as seen in the context of the "background" of the smear. Specifically, cells, cell clusters, bare nuclei, and cytoplasmic fragments are analyzed and the resulting contextual features, slide-averaged "features" and high-resolution features describing single cells are combined to produce a more complete and accurate description of the smear. This description will provide information not obtainable by human visual analysis, which can be used, 1) directly, to ascertain diagnostic clues, and 2) indirectly to make accurate prescreening possible. An extensive pilot study has shown that the contextual analysis provides complementary information to that provided by single cell analysis. That is, where single cell analysis seems to have difficulty, contextual analysis is most accurate - and vice versa. Thus we expect to demonstrate that the combination of our contextual analysis techniques with single cell analysis will give automated Pap smear analysis the additional screening accuracy that is needed. The proposed project is a followup intended to: a) validate the techniques of the pilot study, b) to expand the study to include parameters that provide additional diagnostic and prognostic information, and c) to generate specifications for a system to accomplish the analysis in a routine clinical laboratory environment.

该项目的总体目标是改善自动宫颈癌 涂片图像分析技术足以：1）常规 提供额外的诊断信息，以补充 由人的视觉检查提供，以及2）提供准确的， 具有成本效益的预筛选能力。 通过提供额外的定量诊断信息， 自动化系统将允许执业细胞病理学家 做出更准确、更精细的诊断判断， 可以改善病人的管理 通过提供 实际的预筛选能力，这样的系统将增加 提供保健服务的效率和功效。 目前的自动化子宫颈涂片分析研究只采用 分离细胞的分析和实际的自动化分析， 还没有成为现实 该项目的主要贡献将是 完成图像分析的开发和测试 从细胞和其他物体中提取信息的技术 正如在涂抹的“背景”中所看到的那样。 具体而言，细胞、细胞簇、裸核和细胞质 对片段进行分析并得到上下文特征， 幻灯片平均“特征”和高分辨率特征描述 单个细胞被组合以产生更完整的 对涂片的准确描述。 本说明将提供 人类视觉分析无法获得的信息， 1）直接用于确定诊断线索，2）间接用于 使精确的预筛选成为可能。 一项广泛的试点研究表明， 提供补充信息，以提供单一的 细胞分析 也就是说，单细胞分析似乎 困难，上下文分析是最准确的-反之亦然。 因此，我们希望证明，我们的组合 具有单细胞分析的上下文分析技术将给出 自动巴氏涂片分析，额外的筛查准确性 这是需要的。 拟议项目是一项后续行动，旨在： 试点研究的技术，B）扩大研究范围， 提供额外诊断和预后的参数 信息，以及c）生成系统的规范， 在常规临床实验室完成分析 环境