Optimizing Medical Imaging Systems for Estimation Tasks

优化医学成像系统的估计任务

• 批准号: 6827438
• 负责人: MATTHEW A KUPINSKI
• 金额: $ 25.74万
• 依托单位: UNIVERSITY OF ARIZONA
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-01 至 2007-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6827438
• 关键词: bioimaging /biomedical imaging; biomedical equipment development; clinical biomedical equipment; computer simulation; evaluation /testing; image enhancement; lymph nodes; mathematics; method development; neoplasm /cancer radiodiagnosis; neoplastic process; phantom model; single photon emission computed tomography

DESCRIPTION (provided by applicant): The objective of the proposed research is to develop a rigorous theoretical and experimental framework for the objective assessment of image quality when the tasks in question are medically relevant estimation tasks. We propose to apply this framework to compare different configurations of a specific SPECT (single photon emission computed tomography) imaging system being developed by our collaborators and to optimize the parameters of this system. We will focus on the task of locating small tumors or other focal objects such as sentinel lymph nodes and the task of estimating integrated tumor activity. We envision three stages in the development of a system optimized for a specific task such as tumor-location estimation. The first stage is the simulation of the entire system to determine optimal parameters. The second stage is the validation of the design by building a small system and using it for phantom or small-animal imaging studies. The final stage is to build a full-sized system for human studies. The work we propose will develop methods for addressing the first stage in this process and will result in the ability to design medical imaging systems that maximize observer performance on estimation tasks. For the second stage, we will apply these methods to the tasks of estimating tumor location and integrated tumor activity using newly designed phantoms and experimental data from a small-animal SPECT system. We will not address the third stage of system optimization in this proposal. We will treat estimation tasks in a general, mathematical sense that will allow us to rapidly extend our work to other imaging modalities (including human imaging systems) and to other estimation tasks without difficulty. Ultimately, this research will result in imaging systems that improve the diagnosis and treatment of patients.

描述（由申请人提供）： 所提出的研究的目的是开发一个严格的理论和实验框架，当所讨论的任务是医学相关的估计任务时，用于客观评估图像质量。我们建议应用这个框架来比较我们的合作者正在开发的特定 SPECT（单光子发射计算机断层扫描）成像系统的不同配置，并优化该系统的参数。我们将重点关注定位小肿瘤或其他焦点对象（例如前哨淋巴结）的任务以及估计综合肿瘤活动的任务。我们设想针对肿瘤位置估计等特定任务进行优化的系统开发的三个阶段。第一阶段是对整个系统进行仿真以确定最佳参数。第二阶段是通过构建一个小型系统并将其用于模型或小动物成像研究来验证设计。最后阶段是建立一个完整的人类研究系统。我们提出的工作将开发解决该过程第一阶段的方法，并将导致设计医学成像系统的能力，从而最大限度地提高观察者在估计任务上的表现。在第二阶段，我们将利用新设计的模型和来自小动物 SPECT 系统的实验数据，将这些方法应用于估计肿瘤位置和综合肿瘤活动的任务。我们不会在这个提案中讨论第三阶段的系统优化。我们将从一般的数学意义上来处理估计任务，这将使我们能够毫无困难地将我们的工作快速扩展到其他成像模式（包括人类成像系统）和其他估计任务。最终，这项研究将产生能够改善患者诊断和治疗的成像系统。