课题基金 / 基金详情

RADIONUCLIDES--RADIATION DETECTION AND QUANTIFICATION

RADIONUCLIDES--RADIATION DETECTION AND QUANTIFICATION
放射性核素——辐射检测和定量
批准号:
2007374
负责人:
WILLIAM L ROGERS
金额:
$34.68万
依托单位国家:
美国
项目类别:
财政年份:
1983
资助国家:
美国
项目状态:
已结题
起止时间:
1983-04-01 至 1998-09-07

项目摘要

项目成果

WILLIAM L ROGERS的其他基金

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中文摘要
翻译
这项研究的长期目标是开发方法, 获得改进的放射性同位素定量的仪器 在人类和动物中的分布。SPRINT II是第三代SPECT 作为这一持续努力的一部分而开发的工具。的重点 一个提议是研究两种创新的SPECT成像方法 基于我们以前的工作, 提高数据准确性和改善信噪比: 1.确定在一个过程中获取大脑的顶视图的价值 常规SPECT采集并将该信息合并到 图像重建或参数估计过程。 2.研究用于SPECT成像的康普顿散射孔径, 各种新的第二检测器几何形状和分析系统, 在散射中包括多重散射和偏振效应 光圈将考虑的模型将包括以下可能性: 结合针孔孔径用于成像未散射的光子。对象 依赖和依赖抽样将被考虑,和性能 将与设计用于 相同的视野和相同的几何分辨率在中心的 视野. 这些成像方法的评价将通过分析 下限、模拟和小规模实验。偏置边界将 用于测量图像重建算法的性能, 从这些系统中获取的数据。
英文摘要
The long term goal of this research is to develop methods and instrumentation to obtain improved quantification of the radioisotope distribution in humans and animals. SPRINT II is a third generation SPECT instrument developed as part of this ongoing effort. The focus of this proposal is to investigate two innovative approaches to SPECT imaging based on our previous work which have the potential for measurably increasing data accuracy and improving signal-to-noise ratios: 1. Determine the value of acquiring a vertex view of the brain during a conventional SPECT acquisition and incorporating this information into the image reconstruction or parameter estimation process. 2. Investigate the Compton scatter aperture for SPECT imaging with a variety of new second detector geometries and analyze systems which include multiple scattering and polarization effects in the scatter aperture. Models to be considered will include the possibility of combining a pinhole aperture for imaging unscattered photons. Object dependence and dependence on sampling will be considered, and performance will be compared to conventionally collimated systems designed for the same field of view and the same geometric resolution at the center of the field of view. Evaluation of these imaging methods will be accomplished using analysis of lower bounds, simulation, and small scale experiments. Biased bounds will be used to measure the performance of image reconstruction algorithms for data acquired from these systems.
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