Iterative CT reconstruction via minimizing adaptively reweighted total variation.
Iterative CT reconstruction via minimizing adaptively reweighted total variation.
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DOI：
10.3233/xst-140421
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发表时间：
2014
影响因子：
3
通讯作者：
Lei Zhu;T. Niu;M. Petrongolo
中科院分区：
文献类型：
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作者：
Lei Zhu;T. Niu;M. Petrongolo
背景技术通过总变差（TV）最小化的迭代重建已经在欠采样投影的精确CT成像方面取得了巨大成功。当投影进一步减少时，当前重建中会出现过度平滑伪影，尤其是在结构边界周围。目的 我们提出了一种实用的算法来改进基于极少投影数据的基于电视最小化的 CT 重建。方法基于压缩感知理论，L-0范数方法更适合进一步减少投影视图。为了克服 L-0 范数的非凸优化的计算困难，我们实现了一种自适应加权方案，通过一系列 TV 最小化来近似解决方案，以便在 CT 重建中实际使用。 TV 上的权重被初始化为统一的权重，并根据上次迭代重建图像的梯度自动更改。当在两个连续的重建图像上观察到加权 TV 值之间存在微小差异时，迭代停止。结果我们在数字体模和物理体模上评估了所提出的算法。我们的方法使用 20 个等角投影，将传统电视最小化中的重建误差减少了 5 倍以上，同时提高了空间分辨率。结论 通过在迭代 CT 重建中自适应地重新加权 TV，我们成功地进一步减少了投影数量，以获得相同或更好的图像质量。
BACKGROUND Iterative reconstruction via total variation (TV) minimization has demonstrated great successes in accurate CT imaging from under-sampled projections. When projections are further reduced, over-smoothing artifacts appear in the current reconstruction especially around the structure boundaries. OBJECTIVE We propose a practical algorithm to improve TV-minimization based CT reconstruction on very few projection data. METHOD Based on the theory of compressed sensing, the L-0 norm approach is more desirable to further reduce the projection views. To overcome the computational difficulty of the non-convex optimization of the L-0 norm, we implement an adaptive weighting scheme to approximate the solution via a series of TV minimizations for practical use in CT reconstruction. The weight on TV is initialized as uniform ones, and is automatically changed based on the gradient of the reconstructed image from the previous iteration. The iteration stops when a small difference between the weighted TV values is observed on two consecutive reconstructed images. RESULTS We evaluate the proposed algorithm on both a digital phantom and a physical phantom. Using 20 equiangular projections, our method reduces reconstruction errors in the conventional TV minimization by a factor of more than 5, with improved spatial resolution. CONCLUSIONS By adaptively reweighting TV in iterative CT reconstruction, we successfully further reduce the projection number for the same or better image quality.