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: 8234040
• 负责人: Jovan G Brankov
• 金额: $ 42.44万
• 依托单位: ILLINOIS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-03-15 至 2014-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8234040
• 关键词: Agreement; Algorithms; Cardiac; Cardiology; Clinical; Clinical Data; Clinical Research; Collaborations; Communities; Computer Assisted; Computer software; Data; Data Set; Decision Theory; Defect; Detection; Development; Diagnostic; Evaluation; Evaluation Methodology; Eye; Foundations; Future; Goals; Gold; 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; clinical decision-making; 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（如一般医学成像）中，人们普遍认为成像硬件和算法的进步应以所谓的基于任务的评估标准为指导，即反映成像技术如何影响临床决策的措施。一般来说，人类观察者研究是衡量基于任务的标准的黄金标准；然而，此类研究的费用和复杂性妨碍了它们的常规使用。因此，数值观察者——模拟人类观察者表现的算法——现在被广泛用作人类观察者的替代者。在 SPECT 中，一种特殊的数值观测器，称为通道化霍特林观测器 (CHO)，已经占据了该领域的主导地位。 CHO 是一种检测算法，用于近似人类观察者检测病变的表现；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 根据生成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（有时完全依赖）诸如 CHO 之类的数值观测器，不仅可以验证其最终结果，还可以作为指导硬件或算法优化的品质因数。由于它所发挥的核心作用，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，我们的目标是创建一套数值观察器，以阐明比 CHO 更广泛的临床任务，并且我们将采用一种我们假设比 CHO 更准确的方法。因此，拟议的研究意义重大，因为它将产生一种可能被研究界广泛使用的评估方法，支撑成像硬件和软件的开发。我们将使用所提出的 NO 方法开发一个用于图像质量评估的软件包，并将其免费分发给研究界。作为研究的副产品，拟议的项目还将对主要图像重建算法进行彻底的基于任务的评估，并将回答哪些类型的数据（从简单的模型到临床数据的范围）是数值观察者根据需要执行任务的充分基础的问题。该研究还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）创建一套全面的成像数据和人类观察者分数； 2）根据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器； 3）比较和评估数值观察者； 4) 开发并传播研究计划的副产品。

项目成果

Design and characterization of a dead-time regime enhanced early photon projection imaging system.

• DOI: 10.1063/1.5003620
• 发表时间: 2018-04
• 期刊: The Review of scientific instruments
• 作者: L. Sinha;M. Fogarty;W. Zhou;A. Giudice;J. Brankov;K. Tichauer

Analysis of ideal observer signal detectability in phase-contrast imaging employing linear shift-invariant optical systems.

采用线性平移不变光学系统的相衬成像中理想观察者信号可检测性的分析。

• DOI: 10.1364/josaa.27.002648
• 发表时间: 2010
• 期刊: Journal of the Optical Society of America. A, Optics, image science, and vision
• 作者: Anastasio,MarkA;Chou,Cheng-Ying;Zysk,AdamM;Brankov,JovanG
• 通讯作者: Brankov,JovanG

Full receiver operating characteristic curve estimation using two alternative forced choice studies.

使用两个替代的强制选择研究来估计完整的受试者工作特征曲线。

• DOI: 10.1117/1.jmi.3.1.011010
• 发表时间: 2016
• 期刊: Journal of medical imaging (Bellingham, Wash.)
• 作者: Massanes,Francesc;Brankov,JovanG
• 通讯作者: Brankov,JovanG