FAST FULLY 3D IMAGE RECONSTRUCTION USING PLANOGRAMS

描述(改编自申请人摘要)：本报告的目标 建议是实施和比较评估重建 基于一种新的数据采集格式的算法，该格式被称为“平面图” 这适用于探测器表面平坦的PET扫描仪。这个 平面图算法使用一种固有的数据采集格式 双探头SPECT扫描仪在符合模式下运行。这些扫描仪 作为经济高效的替代品受到了相当大的关注 全身肿瘤学的PET扫描仪，一直在使用 医院的数量不断增加。因此，存在着一个巨大的现有基础 可利用快速准确重建的扫描仪 算法。目前的重建方法无法生成图像 在可行的时间内从符合模式的SPECT扫描仪数据 在统计噪声的准确性或传播方面的权衡。这个 申请者被描述为已经推导出 虽然概念上很复杂，但在计算上却很复杂的航路图格式 简单并允许执行重建计算 完全使用快速傅立叶变换(FFT)。这将允许 符合模式SPECT系统和具有类似平板的PET扫描仪 平板探测器几何结构，以在静止时实现其完全灵敏度 在临床可行的时间内重建图像。预计 可以对平面图算法进行优化以减少图像重建 与目前的技术相比，时间缩短了大约两个数量级， 而不会增加噪声传播或分辨率损失。这个 这项建议的具体目的是：(I)实施和验证 平面图重建算法及(Ii)平面图比较 关于标准三维重建方法的算法 重建时间、精度和统计噪声的降低。这个 这项研究的长期目标是帮助开发 用于临床肿瘤成像的高性价比全身PET扫描仪， 其中，图像重建是一个关键组件。

DESCRIPTION (Adapted from Applicant's Abstract): The goal of this proposal is to implement and comparatively evaluate a reconstruction algorithm based on a new data acquisition format called a "planogram" that is applicable to PET scanners with flat detector surfaces. The planogram algorithm uses a data acquisition format that is intrinsic to dual-head SPECT scanners operated in coincidence mode. These scanners have received considerable attention as cost-effective alternatives to PET scanners for whole-body oncology and are in use at an ever increasing number of hospitals. There is thus a large base of existing scanners that can take advantage of fast and accurate reconstruction algorithm. Current reconstruction methods are unable to generate images from coincident-mode SPECT scanner data in a feasible time without trade-offs in accuracy or propagation of statistical noise. The applicants described having derived mathematical relationships for the planogram format that, while conceptually complex, are computationally simple and allow the reconstruction computations to be performed entirely with fast Fourier transforms (FFTs). This will allow coincidence-mode SPECT systems, and PET scanners with a flat similar plate detector geometry, to realize their full sensitivity while still reconstructing images in a clinically feasible time. It is expected that the planogram algorithm can be optimized to reduce image reconstruction time by about two orders of magnitude, compared to current techniques, without any increase in noise propagation or loss of resolution. The specific aims of this proposal are to (i) implement and validate the planogram reconstruction algorithm and (ii) compare the planogram algorithm to standard 3D reconstruction methods in terms of reconstruction time, accuracy, and reduction o statistical noise. The long-term objective of this research is to assist in the development of cost-effective whole-body PET scanners for clinical oncology imaging, for which the image reconstruction is a critical component.