Brendel Bernhard, von Teuffenbach Maximilian, Noël Peter B, Pfeiffer Franz, Koehler Thomas
Research Laboratories, Philips GmbH Innovative Technologies, Hamburg D-22335, Germany.
Lehrstuhl für Biomedizinische Physik, Physik-Department und Institut für Medizintechnik, Technische Universität München, Garching D-85748, Germany.
Med Phys. 2016 Jan;43(1):188. doi: 10.1118/1.4938067.
The purpose of this work is to propose a cost function with regularization to iteratively reconstruct attenuation, phase, and scatter images simultaneously from differential phase contrast (DPC) acquisitions, without the need of phase retrieval, and examine its properties. Furthermore this reconstruction method is applied to an acquisition pattern that is suitable for a DPC tomographic system with continuously rotating gantry (sliding window acquisition), overcoming the severe smearing in noniterative reconstruction.
We derive a penalized maximum likelihood reconstruction algorithm to directly reconstruct attenuation, phase, and scatter image from the measured detector values of a DPC acquisition. The proposed penalty comprises, for each of the three images, an independent smoothing prior. Image quality of the proposed reconstruction is compared to images generated with FBP and iterative reconstruction after phase retrieval. Furthermore, the influence between the priors is analyzed. Finally, the proposed reconstruction algorithm is applied to experimental sliding window data acquired at a synchrotron and results are compared to reconstructions based on phase retrieval.
The results show that the proposed algorithm significantly increases image quality in comparison to reconstructions based on phase retrieval. No significant mutual influence between the proposed independent priors could be observed. Further it could be illustrated that the iterative reconstruction of a sliding window acquisition results in images with substantially reduced smearing artifacts.
Although the proposed cost function is inherently nonconvex, it can be used to reconstruct images with less aliasing artifacts and less streak artifacts than reconstruction methods based on phase retrieval. Furthermore, the proposed method can be used to reconstruct images of sliding window acquisitions with negligible smearing artifacts.
本研究旨在提出一种带正则化的代价函数，以便从微分相衬（DPC）采集数据中同时迭代重建衰减图像、相位图像和散射图像，无需相位恢复，并研究其特性。此外，这种重建方法应用于适合连续旋转龙门架的DPC断层扫描系统的采集模式（滑动窗口采集），克服了非迭代重建中严重的模糊现象。
我们推导了一种惩罚最大似然重建算法，直接从DPC采集的探测器测量值重建衰减图像、相位图像和散射图像。所提出的惩罚项针对这三张图像中的每一张，包含一个独立的平滑先验项。将所提出的重建方法的图像质量与通过相位恢复后的滤波反投影（FBP）和迭代重建生成的图像进行比较。此外，分析了先验项之间的影响。最后，将所提出的重建算法应用于在同步加速器上采集的实验滑动窗口数据，并将结果与基于相位恢复的重建结果进行比较。
结果表明，与基于相位恢复的重建相比，所提出的算法显著提高了图像质量。未观察到所提出的独立先验项之间有显著的相互影响。此外，可以说明滑动窗口采集的迭代重建产生的图像具有明显减少的模糊伪影。
尽管所提出的代价函数本质上是非凸的，但与基于相位恢复的重建方法相比，它可用于重建具有更少混叠伪影和更少条纹伪影的图像。此外，所提出的方法可用于重建滑动窗口采集的图像，其模糊伪影可忽略不计。
