Low-dose 4DCT reconstruction via temporal nonlocal means
Low-dose 4DCT reconstruction via temporal nonlocal means
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DOI：
10.1118/1.3547724
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发表时间：
2011-03-01
期刊：
影响因子：
3.8
通讯作者：
Jiang, Steve B.
中科院分区：
文献类型：
--
作者：
Tian, Zhen;Jia, Xun;Jiang, Steve B.
目的：四维计算机断层扫描（4DCT）已广泛应用于癌症放射治疗中，用于胸部和上腹部区域肿瘤的精确靶区勾画和运动测量。然而，与常规CT相比，其延长的扫描时间导致辐射剂量的显著增加，这是其临床应用中的主要问题。本文提出了一种新的算法，从低mA s水平下采集的欠采样投影重建4DCT图像，以降低成像剂量。方法：传统的方法是使用滤波反投影（FBP）算法独立重建4DCT的每个相位。作者提出的新算法的基本思想是利用不同相位之间的共同信息，减少重建高质量图像所需的输入信息，从而减少成像剂量。作者提出了一种时间非局部均值（TNLM）方法来探索相间的相似性。通过最小化由数据保真度项和TNLM正则化项组成的代价函数，同时重建4DCT图像的所有相位。作者利用改进的前向-后向分裂算法和高斯-雅可比迭代方法有效地解决了最小化问题。该算法也被实现在一个图形处理单元（GPU），以提高计算速度。作者的重建算法已被测试的数字NCAT胸部体模在三个低剂量的情况下：所有的预测与低mA的水平，欠采样的预测与高mA的水平，欠采样的预测与低mA的level.Results：在所有三个低剂量的情况下，新算法产生的视觉上更好的CT图像包含更少的图像噪声和条纹伪影相比，标准的FBP算法。定量分析表明，作者的TNLM算法与标准的FBP算法相比，对比噪声比提高了3.9-10.2倍，信噪比提高了2.1-5.9倍。在投影数据欠采样的情况下，利用本文提出的算法，可以抑制FBP重建图像中的大部分条纹。在NVIDIA Tesla C1060 GPU卡上，一个切片的所有10个相位的总重建时间范围为40 ~ 90 s。结论：实验结果表明，作者的新算法在有效减少欠采样引起的图像伪影和抑制低mA s电平引起的图像噪声方面优于传统的FBP算法。(C)2011年美国医学物理学家协会。[DOI 10.1118/1.3547724]
Purpose: Four-dimensional computed tomography (4DCT) has been widely used in cancer radiotherapy for accurate target delineation and motion measurement for tumors in the thorax and upper abdomen areas. However, its prolonged scanning duration causes a considerable increase of radiation dose compared to conventional CT, which is a major concern in its clinical application. This work is to develop a new algorithm to reconstruct 4DCT images from undersampled projections acquired at low mA s levels in order to reduce the imaging dose.Methods: Conventionally, each phase of 4DCT is reconstructed independently using the filtered backprojection (FBP) algorithm. The basic idea of the authors' new algorithm is that by utilizing the common information among different phases, the input information required to reconstruct the image of high quality, and thus the imaging dose, can be reduced. The authors proposed a temporal nonlocal means (TNLM) method to explore the interphase similarity. All phases of the 4DCT images are reconstructed simultaneously by minimizing a cost function consisting of a data fidelity term and a TNLM regularization term. The authors utilized a modified forward-backward splitting algorithm and a Gauss-Jacobi iteration method to efficiently solve the minimization problem. The algorithm was also implemented on a graphics processing unit (GPU) to improve the computational speed. The authors' reconstruction algorithm has been tested on a digital NCAT thorax phantom in three low dose scenarios: All projections with low mA s level, undersampled projections with high mA s level, and undersampled projections with low mA s level.Results: In all three low dose scenarios, the new algorithm generates visually much better CT images containing less image noise and streaking artifacts compared to the standard FBP algorithm. Quantitative analysis shows that by comparing the authors' TNLM algorithm to the standard FBP algorithm, the contrast-to-noise ratio has been improved by a factor of 3.9-10.2 and the signal-to-noise ratio has been improved by a factor of 2.1-5.9, depending on the cases. In the situation of undersampled projection data, the majority of the streaks in the images reconstructed by FBP can be suppressed using the authors' algorithm. The total reconstruction time for all ten phases of a slice ranges from 40 to 90 s on an NVIDIA Tesla C1060 GPU card.Conclusions: The experimental results indicate that the authors' new algorithm outperforms the conventional FBP algorithm in effectively reducing the image artifacts due to undersampling and suppressing the image noise due to the low mA s level. (C) 2011 American Association of Physicists in Medicine. [DOI: 10.1118/1.3547724]