Brix G, Doll J, Bellemann M E, Trojan H, Haberkorn U, Schmidlin P, Ostertag H
Research Program "Radiological Diagnostics and Therapy", German Cancer Research Center (DKFZ), Heidelberg, Germany.
Eur J Nucl Med. 1997 Jul;24(7):779-86. doi: 10.1007/BF00879667.
The purpose of this work was to improve of the spatial resolution of a whole-body positron emission tomography (PET) system for experimental studies of small animals by incorporation of scanner characteristics into the process of iterative image reconstruction. The image-forming characteristics of the PET camera were characterized by a spatially variant line-spread function (LSF), which was determined from 49 activated copper-64 line sources positioned over a field of view (FOV) of 21.0 cm. This information was used to model the image degradation process. During the course of iterative image reconstruction, the forward projection of the estimated image was blurred with the LSF at each iteration step before the estimated projections were compared with the measured projections. The imaging characteristics of the high-resolution algorithm were investigated in phantom experiments. Moreover, imaging studies of a rat and two nude mice were performed to evaluate the imaging properties of our approach in vivo. The spatial resolution of the scanner perpendicular to the direction of projection could be approximated by a one-dimensional Gaussian-shaped LSF with a full-width at half-maximum increasing from 6.5 mm at the centre to 6.7 mm at a radial distance of 10.5 cm. The incorporation of this blurring kernel into the iteration formula resulted in a significantly improved spatial resolution of about 3.9 mm over the examined FOV. As demonstrated by the phantom and the animal experiments, the high-resolution algorithm not only led to a better contrast resolution in the reconstructed emission scans but also improved the accuracy for quantitating activity concentrations in small tissue structures without leading to an amplification of image noise or image mottle. The presented data-handling strategy incorporates the image restoration step directly into the process of algebraic image reconstruction and obviates the need for ill-conditioned "deconvolution" procedures to be performed on the projections or on the reconstructed image. In our experience, the proposed algorithm is of special interest in experimental studies of small animals.
这项工作的目的是通过将扫描仪特性纳入迭代图像重建过程，提高用于小动物实验研究的全身正电子发射断层扫描（PET）系统的空间分辨率。PET相机的成像特性由空间可变线扩展函数（LSF）表征，该函数由位于21.0 cm视野（FOV）上的49个活化铜 - 64线源确定。此信息用于对图像退化过程进行建模。在迭代图像重建过程中，在将估计投影与测量投影进行比较之前，估计图像的前向投影在每个迭代步骤都用LSF进行模糊处理。在体模实验中研究了高分辨率算法的成像特性。此外，还对一只大鼠和两只裸鼠进行了成像研究，以评估我们的方法在体内的成像特性。垂直于投影方向的扫描仪空间分辨率可以用一维高斯形状的LSF近似，其半高全宽从中心处的6.5 mm增加到径向距离10.5 cm处的6.7 mm。将此模糊核纳入迭代公式后，在所检查的FOV上空间分辨率显著提高，约为3.9 mm。如体模和动物实验所示，高分辨率算法不仅在重建的发射扫描中带来了更好的对比度分辨率，还提高了小组织结构中活性浓度定量的准确性，而不会导致图像噪声或图像斑点的放大。所提出的数据处理策略将图像恢复步骤直接纳入代数图像重建过程，无需对投影或重建图像执行病态的“反卷积”程序。根据我们的经验，所提出的算法在小动物实验研究中特别有意义。
