Two-dimensional noise reconstruction in proton computed tomography using distance-driven filtered back-projection of simulated projections
Two-dimensional noise reconstruction in proton computed tomography using distance-driven filtered back-projection of simulated projections
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DOI：
10.1088/1361-6560/aae5c9
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发表时间：
2018-11-01
影响因子：
3.5
通讯作者：
Dedes, George
中科院分区：
文献类型：
--
作者：
Raedler, Martin;Landry, Guillaume;Dedes, George
我们提出了一种形式主义的二维（2D）的噪声重建质子计算机断层扫描（pCT）。这对于注量调制pCT（FMpCT）的应用是必要的，因为它允许图像噪声处方和相应的质子注量优化。我们的目的是扩展以前发表的形式主义，以考虑到多重库仑散射（MCS）对投影噪声的影响，并使用过滤反投影（FBP）重建沿着弯曲的路径与距离驱动的分箱（DDB）。2D噪声重建的质子束与平行的初始动量矢量，并在后方跟踪器和DDB分箱的投影，建立。采用水圆柱的pCT扫描的蒙特卡罗（MC）模拟来生成pCT投影并计算其噪声以用于2D噪声重建。这些结果进行了比较，从一个分析模型占MCS后方跟踪器分箱，以及对先前发表的中心像素模型，忽略MCS。将后跟踪器分箱和DDB形式化重建的图像噪声与环形感兴趣区域（ROI）的MC结果进行了比较，MC模拟计算的投影噪声与我们的模型之间的一致性优于8%。来自环形ROI的噪声与我们对后跟踪器分箱和DDB的噪声重建一致。忽略MCS的中心像素模型低估了投影，因此对目标边缘的图像噪声高达40%.DDB的使用减少了对目标边缘的图像噪声相比，后方跟踪器分箱，并产生更均匀的噪声在整个图像。当预测pCT扫描中远离对象中心的像素的图像噪声时，由于更靠近边缘的对象的船体的梯度的影响越来越大，因此不应忽略MCS。
We present a formalism for two-dimensional (2D) noise reconstruction in proton computed tomography (pCT). This is necessary for the application of fluence modulated pCT (FMpCT) since it permits image noise prescription and the corresponding proton fuence optimization. We aimed at extending previously published formalisms to account for the impact of multiple Coulomb scattering (MCS) on projection noise, and the use of filtered back projection (FBP) reconstruction along curved paths with distance driven binning (DDB).2D noise reconstruction for a beam of protons with parallel initial momentum vectors, and for projections binned both at the rear tracker and with DDB, was established. Monte Carlo (MC) simulations of pCT scans of a water cylinder were employed to generate pCT projections and to calculate their noise for use in 2D noise reconstruction. These were compared to results from an analytical model accounting for MCS for rear tracker binning as well as against the previously published central pixel model which ignores MCS. Image noise reconstructed with the formalism for rear tracker binning and DDB were compared to MC results using annular regions of interest (ROIs).Agreement better than 8% was obtained between the noise of projections calculated with MC simulation and our model. Noise from annular ROIs agreed with our noise reconstructions for rear tracker binning and DDB. The central pixel model ignoring MCS underestimated projection and thus image noise by up to 40% towards the object's edge.The use of DDB decreased the image noise towards the object's edge when compared to rear tracker binning and yielded more uniform noise throughout the image. MCS should not be neglected when predicting image noise for pixels away from the center of an object in a pCT scan due to the increasing influence of the gradient of the object's hull closer to the edges.