FAST FULLY 3D IMAGE RECONSTRUCTION USING PLANOGRAMS

描述（改编自申请人的摘要）：本发明的目标是 建议实施并比较评估一个重建 基于称为“货架图”的新数据采集格式的算法 其适用于具有平坦探测器表面的PET扫描仪。的 货架图算法使用固有的数据采集格式， 双头SPECT扫描仪以符合模式运行。这些扫描仪 作为具有成本效益的替代品， PET扫描仪用于全身肿瘤学， 医院数量不断增加。因此，现有的基础很大， 扫描仪可以利用快速准确的重建 算法目前的重建方法无法生成图像 从符合模式SPECT扫描仪数据在可行的时间内， 在准确性或统计噪声传播方面的折衷。的 申请人描述了已经推导出用于 货架图格式，虽然概念上复杂， 简单并允许执行重建计算 快速傅立叶变换（FFT）。这将允许 符合模式SPECT系统和具有类似平面的PET扫描仪 板检测器几何形状，以实现其全部灵敏度，同时仍然 在临床可行的时间内重建图像。预计在 可以优化货架图算法以减少图像重建 时间大约两个数量级，与当前技术相比， 而没有噪声传播的任何增加或分辨率的损失。的 本建议的具体目标是：㈠执行和验证 货架图重建算法和（ii）比较货架图 标准3D重建方法的算法 重建时间、精度和统计噪声的减少。的 这项研究的长期目标是帮助发展 用于临床肿瘤学成像的具有成本效益的全身PET扫描仪， 其中图像重建是关键的组成部分。

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.