Wang Adam S, Stayman J Webster, Otake Yoshito, Vogt Sebastian, Kleinszig Gerhard, Siewerdsen Jeffrey H
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland 21205.
Siemens Healthcare XP Division, Erlangen, 91052, Germany.
Med Phys. 2015 May;42(5):2699-708. doi: 10.1118/1.4914378.
To accelerate model-based iterative reconstruction (IR) methods for C-arm cone-beam CT (CBCT), thereby combining the benefits of improved image quality and/or reduced radiation dose with reconstruction times on the order of minutes rather than hours.
The ordered-subsets, separable quadratic surrogates (OS-SQS) algorithm for solving the penalized-likelihood (PL) objective was modified to include Nesterov's method, which utilizes "momentum" from image updates of previous iterations to better inform the current iteration and provide significantly faster convergence. Reconstruction performance of an anthropomorphic head phantom was assessed on a benchtop CBCT system, followed by CBCT on a mobile C-arm, which provided typical levels of incomplete data, including lateral truncation. Additionally, a cadaveric torso that presented realistic soft-tissue and bony anatomy was imaged on the C-arm, and different projectors were assessed for reconstruction speed.
Nesterov's method provided equivalent image quality to OS-SQS while reducing the reconstruction time by an order of magnitude (10.0 ×) by reducing the number of iterations required for convergence. The faster projectors were shown to produce similar levels of convergence as more accurate projectors and reduced the reconstruction time by another 5.3 ×. Despite the slower convergence of IR with truncated C-arm CBCT, comparison of PL reconstruction methods implemented on graphics processing units showed that reconstruction time was reduced from 106 min for the conventional OS-SQS method to as little as 2.0 min with Nesterov's method for a volumetric reconstruction of the head. In body imaging, reconstruction of the larger cadaveric torso was reduced from 159 min down to 3.3 min with Nesterov's method.
The acceleration achieved through Nesterov's method combined with ordered subsets reduced IR times down to a few minutes. This improved compatibility with clinical workflow better enables broader adoption of IR in CBCT-guided procedures, with corresponding benefits in overcoming conventional limits of image quality at lower dose.
加速基于模型的迭代重建（IR）方法用于C型臂锥束CT（CBCT），从而将图像质量提高和/或辐射剂量降低的益处与几分钟而非几小时的重建时间相结合。
对用于求解惩罚似然（PL）目标的有序子集、可分离二次替代（OS-SQS）算法进行修改，纳入Nesterov方法，该方法利用前几次迭代的图像更新中的“动量”来更好地指导当前迭代并显著加快收敛速度。在台式CBCT系统上评估了拟人化头部模型的重建性能，随后在移动C型臂上进行CBCT，该系统提供了包括横向截断在内的典型不完全数据水平。此外，在C型臂上对呈现逼真软组织和骨骼解剖结构的尸体躯干进行成像，并评估不同的投影器以确定重建速度。
Nesterov方法在提供与OS-SQS相当的图像质量的同时，通过减少收敛所需的迭代次数将重建时间缩短了一个数量级（10.0倍）。结果表明，速度更快的投影器与更精确的投影器产生的收敛水平相似，并将重建时间再减少了5.3倍。尽管截断的C型臂CBCT的IR收敛较慢，但在图形处理单元上实现的PL重建方法的比较表明，对于头部的容积重建，传统OS-SQS方法的重建时间从106分钟减少到使用Nesterov方法时低至2.0分钟。在人体成像中，使用Nesterov方法将较大尸体躯干的重建时间从159分钟减少到3.3分钟。
通过Nesterov方法与有序子集相结合实现的加速将IR时间缩短至几分钟。这改善了与临床工作流程的兼容性，更好地促进了IR在CBCT引导程序中的更广泛应用，并在以较低剂量克服传统图像质量限制方面具有相应益处。
