Low-dose CT reconstruction via edge-preserving total variation regularization.
Low-dose CT reconstruction via edge-preserving total variation regularization.
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DOI：
10.1088/0031-9155/56/18/011
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发表时间：
2011-09-21
影响因子：
3.5
通讯作者：
Jiang SB
中科院分区：
文献类型：
--
作者：
Tian Z;Jia X;Yuan K;Pan T;Jiang SB
CT扫描中的高辐射剂量会增加终身患癌症的风险，并已成为一个主要的临床问题。近年来，为了减少成像剂量，人们提出了基于总变差(TV)正则化的迭代重建算法，用于从低mAs采集的高欠采样数据中重建CT图像。尽管如此，低对比度的结构往往会被电视正则化所平滑，这对电视方法提出了巨大的挑战。为了解决这一问题，本文提出了一种基于边缘保持TV正则化的迭代CT重建算法，用于从低mAs水平的高欠采样数据中重建CT图像。通过最小化由边缘保持TV范数和由X射线投影构成的数据保真项组成的能量来重建CT图像。为了更好地保持图像的边缘，提出了保持边缘的TV项，通过在原始的全变差范数中引入惩罚权值，优先对图像的非边缘部分进行平滑。在重建过程中，将逐步识别边缘像素，并赋予较小的惩罚权重。我们的迭代算法在GPU上实现，以提高其速度。我们在一个NCAT数字体模、一个物理胸部体模和一个Catphan体模上测试了我们的重建算法。为了便于比较，文中还给出了常规FBP算法和无边缘保持惩罚的TV正则化方法的重建结果。实验结果表明，在低剂量环境下，基于TV的算法和保持边缘的TV算法在抑制条纹伪影和图像噪声方面都优于传统的FBP算法。我们的边缘保持算法优于基于TV的算法，因为它可以保留更多的低对比度结构的信息，从而保持可接受的空间分辨率。
High radiation dose in CT scans increases a lifetime risk of cancer and has become a major clinical concern. Recently, iterative reconstruction algorithms with Total Variation (TV) regularization have been developed to reconstruct CT images from highly undersampled data acquired at low mAs levels in order to reduce the imaging dose. Nonetheless, the low contrast structures tend to be smoothed out by the TV regularization, posing a great challenge for the TV method. To solve this problem, in this work we develop an iterative CT reconstruction algorithm with edge-preserving TV regularization to reconstruct CT images from highly undersampled data obtained at low mAs levels. The CT image is reconstructed by minimizing an energy consisting of an edge-preserving TV norm and a data fidelity term posed by the x-ray projections. The edge-preserving TV term is proposed to preferentially perform smoothing only on non-edge part of the image in order to better preserve the edges, which is realized by introducing a penalty weight to the original total variation norm. During the reconstruction process, the pixels at edges would be gradually identified and given small penalty weight. Our iterative algorithm is implemented on GPU to improve its speed. We test our reconstruction algorithm on a digital NCAT phantom, a physical chest phantom, and a Catphan phantom. Reconstruction results from a conventional FBP algorithm and a TV regularization method without edge preserving penalty are also presented for comparison purpose. The experimental results illustrate that both TV-based algorithm and our edge-preserving TV algorithm outperform the conventional FBP algorithm in suppressing the streaking artifacts and image noise under the low dose context. Our edge-preserving algorithm is superior to the TV-based algorithm in that it can preserve more information of low contrast structures and therefore maintain acceptable spatial resolution.
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影响因子：
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作者：
Berrington de González A;Mahesh M;Kim KP;Bhargavan M;Lewis R;Mettler F;Land C
通讯作者：
Land C
影响因子：
3.5
作者：
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通讯作者：
Jiang, Steve B.
影响因子：
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通讯作者：
Owens, John D.
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作者：
RUDIN, LI;OSHER, S;FATEMI, E
通讯作者：
FATEMI, E
影响因子：
3.5
作者：
Gu, Xuejun;Choi, Dongju;Jiang, Steve B.
通讯作者：
Jiang, Steve B.