New Class of Numerical Observers for Nuclear Cardiology

核心脏病学的新一类数值观察者

• 批准号: 7837005
• 负责人: Jovan G Brankov
• 金额: $ 22.95万
• 依托单位: ILLINOIS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-15 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7837005
• 关键词: Agreement; Algorithms; Cardiac; Cardiology; Clinical; Clinical Data; Clinical Research; Collaborations; Communities; Computer Assisted; Computer software; Data; Data Set; Decision Making; Decision Theory; Defect; Detection; Development; Diagnostic; Evaluation; Evaluation Methodology; Eye; Foundations; Future; Goals; Gold; Hand; Human; Hybrids; Illinois; Image; Image Analysis; Imaging Techniques; Institutes; Joints; Knowledge; Learning; Lesion; Light; Machine Learning; Maps; Massachusetts; Measures; Medical; Medical Imaging; Methodology; Methods; Modeling; Motion; Myocardial perfusion; Myocardium; Nuclear; Outcome; Output; Performance; Perfusion; Play; Process; Property; Publications; Recording of previous events; Research; Research Personnel; Research Project Grants; Role; Severities; Simulate; Solutions; Sorting - Cell Movement; System; Techniques; Technology; Testing; Tissue Viability; Training; Universities; Ursidae Family; base; computer program; experience; flexibility; human data; image reconstruction; interest; medical schools; novel; novel strategies; programs; response; single photon emission computed tomography; standard measure; success; tool

DESCRIPTION (provided by applicant): Single-photon emission computed tomography (SPECT) imaging has become a standard component of modern cardiology. In SPECT research (as in medical imaging generally), it has become widely accepted that advances in imaging hardware and algorithms should be guided by so-called task-based evaluation criteria, i.e., measures that reflect how the imaging technique will impact clinical decision making. In general, a human observer study is the gold standard for measuring task-based criteria; however, the expense and complexity of such studies precludes their routine use. Therefore, numerical observers-algorithms that emulate human observer performance-are now widely used as surrogates for human observers. In SPECT, one particular numerical observer, known as the channelized Hotelling observer (CHO), has come to dominate the field. The CHO is a detection algorithm that is used to approximate the human observer's performance in detecting lesions; in the case of cardiac SPECT, the lesions of interest are perfusion defects. An imaging system or algorithm can be judged by the ability of the CHO to accurately detect defects based on the images produced. SPECT researchers now rely heavily (and sometimes exclusively) on numerical observers such as the CHO, not only to validate their final results, but also as a figure of merit that guides optimization of hardware or algorithms. Because of the central role it has come to play, the CHO and its extensions have become a major research topic in their own right. In the proposed project, our goal will be to create a suite of numerical observers that will shed light on a much wider set of clinical tasks than the CHO, and we will pursue an approach that we hypothesize will be more accurate than the CHO. Therefore, the proposed research is significant because it will yield an evaluation methodology that could potentially be used very widely by the research community, underpinning the development of imaging hardware and software. We will develop a software package for image quality assessment using the proposed NO approach and distribute it freely to the research community. As a by-product of the research, the proposed project will also yield a thorough task-based evaluation of major image reconstruction algorithms, and will answer the question of which sorts of data (on the spectrum from simple phantoms to clinical data) are a sufficient foundation for numerical observers to perform as desired. The research will also yield the basis for a potential computer aided diagnostic system for cardiology. The specific aims of the research will be as follows: 1) Create a comprehensive set of imaging data and human observer scores; 2) Develop a suite of numerical observers based on our novel learning-based approach, as well as more-conventional statistical decision theory principles; 3) Compare and evaluate the numerical observers; and 4) Develop and disseminate by-products of the research program.

描述（由申请人提供）：单光子发射计算机断层扫描（SPECT）成像已成为现代心脏病学的标准组成部分。在SPECT研究中（如通常在医学成像中），成像硬件和算法的进步应该由所谓的基于任务的评估标准指导，即，反映成像技术将如何影响临床决策的措施。一般来说，人类观察员研究是衡量基于任务的标准的黄金标准;然而，这种研究的费用和复杂性排除了它们的常规使用。因此，数值模拟器-模拟人类观察者性能的算法-现在被广泛用作人类观察者的替代品。在SPECT中，一个特定的数值观测器，被称为通道化霍特林观测器（CHO），已经成为该领域的主导。CHO是一种检测算法，用于近似人类观察者检测病变的性能;在心脏SPECT的情况下，感兴趣的病变是灌注缺陷。成像系统或算法可以通过CHO基于产生的图像准确检测缺陷的能力来判断。SPECT研究人员现在严重依赖（有时是完全依赖）CHO等数值观测器，不仅用于验证他们的最终结果，而且还作为指导硬件或算法优化的优值。由于它所扮演的核心角色，CHO及其扩展本身已成为一个主要的研究课题。在拟议的项目中，我们的目标将是创建一套数值观察器，这些观察器将揭示比CHO更广泛的临床任务，我们将追求一种我们假设比CHO更准确的方法。因此，拟议的研究是重要的，因为它将产生一个评估方法，可能会被研究界非常广泛地使用，支撑成像硬件和软件的发展。我们将开发一个软件包的图像质量评估使用建议的NO方法，并免费分发给研究界。作为研究的副产品，该项目还将对主要的图像重建算法进行基于任务的全面评估，并将回答哪些类型的数据（从简单的幻影到临床数据）是数值观察者按需执行的充分基础。这项研究也将为潜在的心脏病学计算机辅助诊断系统奠定基础。研究的具体目标如下：1）创建一组全面的成像数据和人类观察者评分; 2）基于我们新颖的基于学习的方法以及更传统的统计决策理论原理开发一套数值观察者; 3）比较和评估数值观察者; 4）开发和传播研究计划的副产品。