Prior image constrained compressed sensing (PICCS): A method to accurately reconstruct dynamic CT images from highly undersampled projection data sets
Prior image constrained compressed sensing (PICCS): A method to accurately reconstruct dynamic CT images from highly undersampled projection data sets
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DOI：
10.1118/1.2836423
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发表时间：
2008-02-01
期刊：
影响因子：
3.8
通讯作者：
Leng, Shuai
中科院分区：
文献类型：
--
作者：
Chen, Guang-Hong;Tang, Jie;Leng, Shuai
当投影数不满足Shannon/Nyquist采样要求时，在使用滤波反投影算法重建的X射线计算机断层扫描（CT）图像中不可避免地会出现条纹伪影。本文利用动态CT图像的时空相关性对动态CT图像序列进行稀疏化处理。采用新提出的压缩感知（CS）重构方法对目标图像序列进行重构。利用从交织的动态数据集的并集重建的先验图像来约束针对各个时间帧的CS图像重建。这种方法被称为先验图像约束压缩感知（PICCS）。进行了体内实验动物研究以验证PICCS算法，结果表明PICCS能够使用约20个视角准确重建动态CT图像，这对应于欠采样因子32。该欠采样因子意味着在心肌CT灌注成像中潜在的辐射剂量减少了32倍。(C)2008年美国医学物理学家协会。
When the number of projections does not satisfy the Shannon/Nyquist sampling requirement, streaking artifacts are inevitable in x-ray computed tomography (CT) images reconstructed using filtered backprojection algorithms. In this letter, the spatial-temporal correlations in dynamic CT imaging have been exploited to sparsify dynamic CT image sequences and. the newly proposed compressed sensing (CS) reconstruction method is applied to reconstruct the target image sequences. A prior image reconstructed from the union of interleaved dynamical data sets is utilized to constrain the CS image reconstruction for the individual time frames. This method is referred to as prior image constrained compressed sensing (PICCS). In vivo experimental animal studies were conducted to validate the PICCS algorithm, and the results indicate that PICCS enables accurate reconstruction of dynamic CT images using about 20 view angles, which corresponds to an undersampling factor of 32. This undersampling factor implies a potential radiation dose reduction by a factor of 32 in myocardial CT perfusion imaging. (C) 2008 American Association of Physicists in Medicine.