Automatic Quantification of High S:N Images Using VCS

使用 VCS 自动量化高 S:N 图像

• 批准号: 6694953
• 负责人: PETER Randolph MOUTON
• 金额: $ 9.88万
• 依托单位: STEREOLOGY RESOURCE CENTER, INC.
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-07-10 至 2004-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6694953
• 关键词: animal tissue; automated data processing; bioimaging /biomedical imaging; computer human interaction; computer system design /evaluation; data collection; human tissue; image processing; method development; microscopy

DESCRIPTION (provided by applicant): Theoretically unbiased stereology has been applied to the morphometric analysis of biological tissue sections in the Stereologer, a commercially available, integrated hardware-software-microscopy system. A general limitation of this and other such systems lies in the time- and labor-intensive requirement for identification of targeted objects by trained non-expert users. This Phase 1 SBIR will test the accuracy, efficiency, and feasibility of a novel modification -- Verified Computerized Stereoanalysis (VCS) - for automatic quantification of stereological parameters for objects with a high signal-to-noise ratio (S:N). This automatic combination of image analysis and unbiased stereology will be implemented on the Stereologer system and evaluated through a two-step process: systematic-random sampling under automatic stage control; and, automatic quantification of mean object size and variation. To avoid the collection of spurious data, a verification process after step one will ensure that minimal S:N of equal to or > 90% exists prior to automatic data collection. Accuracy will be evaluated through parallel automatic and semi-automatic analyses on routine tissue sections and by external beta test sites. The VCS approach has the potential to drastically improve throughput of stereological studies, without a loss of accuracy, and thereby stimulate progress in a wide range of biomedical research projects.

描述（由申请人提供）： 理论上无偏的立体论已应用于立体组织中生物组织切片的形态计量学分析，这是一种市售的，集成的硬件软件 - 微观显微镜系统。对此系统和其他此类系统的一般局限性在于时间和劳动密集型要求，以通过训练有素的非专家用户识别目标对象。该阶段1 SBIR将测试新修饰的精度，效率和可行性 - 经过验证的计算机立体分析（VCS） - 自动量化具有较高信噪比（S：N）的物体的立体参数。图像分析和公正的立体论的这种自动组合将在立体系统上实现，并通过两步过程进行评估：在自动阶段控制下进行系统的随机抽样；并且，自动量化平均物体大小和变化。为了避免收集虚假数据，第一个验证过程将确保在自动数据收集之前存在最小的s：n等于或> 90％。将通过对常规组织切片和外部Beta测试位点的平行自动和半自动分析来评估准确性。 VCS方法有可能大幅度改善立体研究的吞吐量，而不会丧失准确性，从而刺激了广泛的生物医学研究项目的进步。