Strategy of computed tomography sinogram inpainting based on sinusoid-like curve decomposition and eigenvector-guided interpolation.
Strategy of computed tomography sinogram inpainting based on sinusoid-like curve decomposition and eigenvector-guided interpolation.
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DOI：
10.1364/josaa.29.000153
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
Yinsheng Li;Yang Chen;Yining Hu;A. Oukili;L. Luo;Wufan Chen;C. Toumoulin
中科院分区：
文献类型：
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作者：
Yinsheng Li;Yang Chen;Yining Hu;A. Oukili;L. Luo;Wufan Chen;C. Toumoulin
x射线计算机断层扫描（CT）中的投影不完全性通常与稀疏采样或检测器间隙有关，并导致严重的条纹和环状伪影的退化重建。为了抑制这些伪影，本研究提出了一种基于类正弦曲线分解和特征向量引导插值的新sinogram inpainting策略，其中每个缺失的sinogram point被认为位于一组类正弦曲线中，并从特征向量引导插值中估计，以保持sinogram纹理的连续性。在真实的二维扇形波束CT数据上对该方法进行了评估，并模拟了由于稀疏采样和对称检测器间隙导致的投影不完全性。在正弦波拟合和插值运算中采用了基于CUDA的并行化处理，加快了算法的速度。然后进行了对比研究，以评估该方法与其他两种涂漆方法和压缩感知迭代重建。定性和定量性能表明，该方法可以有效地抑制伪影，减少结构模糊。
Projection incompleteness in x-ray computed tomography (CT) often relates to sparse sampling or detector gaps and leads to degraded reconstructions with severe streak and ring artifacts. To suppress these artifacts, this study develops a new sinogram inpainting strategy based on sinusoid-like curve decomposition and eigenvector-guided interpolation, where each missing sinogram point is considered located within a group of sinusoid-like curves and estimated from eigenvector-guided interpolation to preserve the sinogram texture continuity. The proposed approach is evaluated on real two-dimensional fan-beam CT data, for which the projection incompleteness, due to sparse sampling and symmetric detector gaps, is simulated. A Compute Unified Device Architecture (CUDA)-based parallelization is applied on the operations of sinusoid fittings and interpolations to accelerate the algorithm. A comparative study is then conducted to evaluate the proposed approach with two other inpainting methods and with a compressed sensing iterative reconstruction. Qualitative and quantitative performances demonstrate that the proposed approach can lead to efficient artifact suppression and less structure blurring.