The point-spread-functions (PSFs) of reconstructed images can be deformed due to detector effects such as resolution blurring and parallax error, data acquisition geometry such as insufficient sampling or limited angular coverage in dual-panel PET systems, or reconstruction imperfections/simplifications. PSF deformation decreases quantitative accuracy and its spatial variation lowers consistency of lesion uptake measurement across the imaging field-of-view (FOV). This can be a significant problem with dual panel PET systems even when using TOF data and image reconstruction models of the detector and data acquisition process. To correct for the spatially variant reconstructed PSF distortions we propose to use an image-based resolution model (IRM) that includes such image PSF deformation effects. Originally the IRM was mostly used for approximating data resolution effects of standard PET systems with full angular coverage in a computationally efficient way, but recently it was also used to mitigate effects of simplified geometric projectors. Our work goes beyond this by including into the IRM reconstruction imperfections caused by combination of the limited angle, parallax errors, and any other (residual) deformation effects and testing it for challenging dual panel data with strongly asymmetric and variable PSF deformations. We applied and tested these concepts using simulated data based on our design for a dedicated breast imaging geometry (B-PET) consisting of dual-panel, time-of-flight (TOF) detectors. We compared two image-based resolution models; i) a simple spatially invariant approximation to PSF deformation, which captures only the general PSF shape through an elongated 3D Gaussian function, and ii) a spatially variant model using a Gaussian mixture model (GMM) to more accurately capture the asymmetric PSF shape in images reconstructed from data acquired with the B-PET scanner geometry. Results demonstrate that while both IRMs decrease the overall uptake bias in the reconstructed image, the second one with the spatially variant and accurate PSF shape model is also able to ameliorate the spatially variant deformation effects to provide consistent uptake results independent of the lesion location within the FOV.

中文翻译：

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基于图像的 PSF 变形建模，适用于有限角度的 PET 数据

重建图像的点扩展函数 (PSF) 可能会由于检测器效应（例如分辨率模糊和视差误差）、数据采集几何结构（例如采样不足或双面板 PET 系统中的角度覆盖范围有限）或重建缺陷/简化而变形. PSF 变形降低了定量精度，其空间变化降低了整个成像视场 (FOV) 病变摄取测量的一致性。即使在使用探测器和数据采集过程的 TOF 数据和图像重建模型时，这也可能是双面板 PET 系统的一个重大问题。为了纠正空间变化的重建 PSF 失真，我们建议使用基于图像的分辨率模型 (IRM)，其中包括此类图像 PSF 变形效果。最初，IRM 主要用于以计算效率高的方式近似具有全角覆盖的标准 PET 系统的数据分辨率效果，但最近它也用于减轻简化几何投影仪的影响。我们的工作超越了这一点，将有限角度、视差误差和任何其他（残余）变形效应的组合引起的 IRM 重建缺陷包括在内，并测试它以挑战具有强不对称和可变 PSF 变形的双面板数据。我们使用模拟数据应用并测试了这些概念，这些数据基于我们为由双面板飞行时间 (TOF) 探测器组成的专用乳房成像几何 (B-PET) 设计。我们比较了两种基于图像的分辨率模型；i) 对 PSF 变形的简单空间不变近似，它通过延长的 3D 高斯函数仅捕获一般 PSF 形状，以及 ii) 使用高斯混合模型 (GMM) 的空间变体模型，以更准确地捕获从使用 B-PET 扫描仪几何结构获取的数据重建的图像中的非对称 PSF 形状. 结果表明，虽然两种 IRM 都降低了重建图像中的整体摄取偏差，但具有空间变异和准确 PSF 形状模型的第二个 IRM 也能够改善空间变异变形效应，以提供与病变位置无关的一致摄取结果视场。ii) 使用高斯混合模型 (GMM) 的空间变体模型，以更准确地捕获从使用 B-PET 扫描仪几何结构获取的数据重建的图像中的非对称 PSF 形状。结果表明，虽然两种 IRM 都降低了重建图像中的整体摄取偏差，但具有空间变异和准确 PSF 形状模型的第二个 IRM 也能够改善空间变异变形效应，以提供与病变位置无关的一致摄取结果视场。ii) 使用高斯混合模型 (GMM) 的空间变体模型，以更准确地捕获从使用 B-PET 扫描仪几何结构获取的数据重建的图像中的非对称 PSF 形状。结果表明，虽然两种 IRM 都降低了重建图像中的整体摄取偏差，但具有空间变异和准确 PSF 形状模型的第二个 IRM 也能够改善空间变异变形效应，以提供与病变位置无关的一致摄取结果视场。