基于GPU的欠采样噪声投影数据快速锥束CT全变分重建
GPU-based Fast Cone Beam CT Reconstruction from Undersampled and Noisy Projection Data via Total Variation
摘要：
目的：锥形束CT（CBCT）在图像引导放射治疗（IGRT）中起着重要作用。然而，在大多数IGRT程序中，连续CBCT扫描的大辐射剂量引起了临床关注，特别是对于由于这个原因基本上被排除接受IGRT的儿科患者。本文的目标是开发一种基于GPU的快速算法，从欠采样和噪声投影数据中重建CBCT，以降低成像剂量。方法：通过最小化由数据保真度项和全变分正则化项组成的能量泛函来重建CBCT。我们开发了一个GPU友好版本的前向-后向分裂算法来解决这个模型。还采用了多重网格技术。结果：20~40张X线投影就足以重建出质量满意的IGRT图像。在NVIDIA Tesla C1060 GPU卡上的重建时间范围从77秒到130秒，取决于所使用的投影数量，估计比类似的迭代重建方法快100倍。此外，体模研究表明，我们的算法使CBCT下重建的扫描协议低至0.1 mAs/投影。与目前广泛使用的全扇形头颈部扫描方案（约360个投影，0.4 mAs/投影）相比，估计我们的快速CBCT重建算法实现了36~72倍的剂量减少。结论：这项工作表明，开发的基于GPU的CBCT重建算法能够大大降低成像剂量。该算法的高计算效率使得迭代CBCT重建方法适用于实际临床环境。
英文摘要：
Purpose: Cone-beam CT (CBCT) plays an important role in image guided radiation therapy (IGRT). However, the large radiation dose from serial CBCT scans in most IGRT procedures raises a clinical concern, especially for pediatric patients who are essentially excluded from receiving IGRT for this reason. The goal of this work is to develop a fast GPU-based algorithm to reconstruct CBCT from undersampled and noisy projection data so as to lower the imaging dose. Methods: The CBCT is reconstructed by minimizing an energy functional consisting of a data fidelity term and a total variation regularization term. We developed a GPU-friendly version of the forward-backward splitting algorithm to solve this model. A multi-grid technique is also employed. Results: It is found that 20~40 x-ray projections are sufficient to reconstruct images with satisfactory quality for IGRT. The reconstruction time ranges from 77 to 130 sec on a NVIDIA Tesla C1060 GPU card, depending on the number of projections used, which is estimated about 100 times faster than similar iterative reconstruction approaches. Moreover, phantom studies indicate that our algorithm enables the CBCT to be reconstructed under a scanning protocol with as low as 0.1 mAs/projection. Comparing with currently widely used full-fan head and neck scanning protocol of ~360 projections with 0.4 mAs/projection, it is estimated that an overall 36~72 times dose reduction has been achieved in our fast CBCT reconstruction algorithm. Conclusions: This work indicates that the developed GPU-based CBCT reconstruction algorithm is capable of lowering imaging dose considerably. The high computation efficiency in this algorithm makes the iterative CBCT reconstruction approach applicable in real clinical environments.
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