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arXiv 1010.1663physics.med-phmath.OC
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质子计算机断层成像图像重建中的全变分优化方案

Total variation superiorization schemes in proton computed tomography image reconstruction

S. N. Penfold, R. W. Schulte, Y. Censor, A. B. Rosenfeld

摘要:

目的:迭代投影重建算法是目前质子计算机断层成像(pCT)的首选重建方法。然而,由于质子能量离散和多次库仑散射引起的测量数据的不一致性,重建图像中的噪声随着连续迭代而增加。在目前的工作中,我们研究了使用全变差优化(TVS)计划,可以作为一个算法的附加扰动弹性迭代投影算法的pCT图像重建。研究方法:块迭代对角松弛正交投影(DROP)算法用于重建Geant 4 Monte Carlo模拟pCT数据集。两个TVS计划添加到DROP进行了研究,第一次进行了superiorization的步骤,每个周期一次,第二次每个块一次。这些计划的简化,包括消除计算昂贵的可行性邻近检查步骤的TVS框架,也进行了研究。调制传递函数和对比度判别函数分别用于量化空间和密度分辨率。结果:与标准DROP算法相比,这两种TVS方案实现了更高的空间和密度分辨率。消除可行性邻近检查提高了图像质量,特别是图像噪声,在每块一次的优越化,同时也减半图像重建时间。总体而言,当每个组织块执行一次优越化并消除可行性邻近检查时,观察到最佳图像质量。结论:TVS使低对比度成像成为可能,有望将其纳入我们未来的pCT研究。

英文摘要:

Purpose: Iterative projection reconstruction algorithms are currently the preferred reconstruction method in proton computed tomography (pCT). However, due to inconsistencies in the measured data arising from proton energy straggling and multiple Coulomb scattering, noise in the reconstructed image increases with successive iterations. In the current work, we investigated the use of total variation superiorization (TVS) schemes that can be applied as an algorithmic add-on to perturbation-resilient iterative projection algorithms for pCT image reconstruction. Methods: The block-iterative diagonally relaxed orthogonal projections (DROP) algorithm was used for reconstructing Geant4 Monte Carlo simulated pCT data sets. Two TVS schemes added on to DROP were investigated; the first carried out the superiorization steps once per cycle and the second once per block. Simplifications of these schemes, involving the elimination of the computationally expensive feasibility proximity checking step of the TVS framework, were also investigated. The modulation transfer function and contrast discrimination function were used to quantify spatial and density resolution, respectively. Results: With both TVS schemes, superior spatial and density resolution was achieved compared to the standard DROP algorithm. Eliminating the feasibility proximity check improved the image quality, in particular image noise, in the once-per-block superiorization, while also halving image reconstruction time. Overall, the greatest image quality was observed when carrying out the superiorization once-per-block and eliminating the feasibility proximity check. Conclusions: The low contrast imaging made possible with TVS holds a promise for its incorporation into our future pCT studies.

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