ESTIMATION STRATEGIES FOR NUCLEAR MEDICAL IMAGING

这项研究的长期目标是开发体内 小动物体内放射性同位素定位的定量， 加速和简化新型放射性标记的设计和评估 大药厂 作为另一个项目的一部分，我们正在完成一个 高分辨率单光子环形断层扫描仪仿照SPRINT，但 专门设计用于小鼠和大鼠的99 mTc、123 I和131 I成像 毫米分辨率。 这一新提案的重点是发展 和评估数据采集策略，下限，和图像 用于以下特定任务目标的重建算法 首先是小动物： 1.总器官或肿瘤摄取。 2.肿瘤和器官剂量分布。 性能限制和估计策略将制定这些 任务都适用于有辅助信息可用的情况，例如， 准确估计器官和肿瘤边界的形式，以及在没有 这些资料是有的。 与不受约束的图像任务不同， 重建，这些任务涉及的特定任务数量少得多， 待估计的参数，因此更好的估计器统计 稳定性是可以期待的。 对这些参数的估计将首先 根据使用约束E-M重建的完整图像计算， 广义Landweber迭代算法 基于预测数据 最小可实现估计均方误差的界限将用于 优化数据采集，以便在 准直器分辨率和灵敏度相对于性能的 具体评估任务。

The long term aim of this research is to develop techniques for in vivo quantification of radioisotope localization in small animals in order to speed and simplify the design and evaluation of new radiolabeled pharmaceuticals. As part of another project we are completing construction of a high-resolution single photon ring tomograph modeled after SPRINT, but specifically designed for imaging 99mTc, 123I, and 131I in mice and rats with millimeter resolution. The focus of this new proposal is development and evaluation of data acquisition strategies, lower bounds, and image reconstruction algorithms for the following taskspecific objectives related initially to small animals: 1. Total organ or tumor uptake. 2. Tumor and organ dose distribution. Performance limits and estimation strategies will be developed for these tasks both for the case where there is side information available, e.g. in the form of accurate estimates of organ and tumor boundaries, and where no such information is available. Unlike the task of unconstrained image reconstruction, these tasks involve a much smaller number of task-specific parameters to be estimated and therefore better estimator statistical stability can be expected. Estimates of these parameters will initially be calculated from complete images reconstructed using constrained E-M and generalized Landweber iterative algorithms. Projection-data based lower bounds on minimum achievable estimator mean-square- error will be used to optimize data acquisition so as to provide the best tradeoff between collimator resolution and sensitivity relative to the performance of a specific estimation task.