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Efficient Methodology for 3D Statistical Reconstruction of High Resolution Coplanar PET/CT Scanner

机译:高分辨率COPLANAR PET / CT扫描仪3D统计重建的高效方法

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A fully 3D statistical image reconstruction algorithm has been developed for a high-resolution coplanar PET/CT scanner based on rotating planar PET detectors. The system matrix has been modeled with custom Monte Carlo techniques optimized for the specific scanner architecture. The system model includes positron range, non-colinearity of gamma rays and crystal interaction modelling with attenuation and Compton scattering effects. Only 0.21% of the system matrix columns are modeled in detail, obtaining the rest of the values with axial and transaxial voxel-driven symmetries. The iterative algorithm is a fully 3D approach, regularized with the anatomical registered image using a novel version of the minimum cross entropy (MXE) scheme, and accelerated employing ordered subsets. The proposed method has been shown to produce images with superior quality than 3D hybrid (FORE+2D-OSEM) algorithms applied on synthetic GATE data, as well as on real small animal acquisitions.
机译:已经为基于旋转平面PET检测器开发了一个完全3D统计图像重建算法,用于高分辨率共面宠物/ CT扫描仪。系统矩阵已为针对特定扫描仪架构进行优化的自定义Monte Carlo技术进行建模。系统模型包括正电子范围,伽马射线的非活性性和晶体交互建模,伴有衰减和康普顿散射效果。只有0.21%的系统矩阵列进行详细建模,以轴向和颠轴驱动的对称获取其余值。迭代算法是一种完全3D方法,使用凹陷登记图像使用新颖的跨熵(MXE)方案进行解剖学登记的图像,并加速采用有序子集。所提出的方法已被证明是在合成门数据上应用于3D混合(前+ 2D-OSEM)算法的卓越品质的图像,以及真正的小动物采集。

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