基于选择性全变差约束的稀疏角度CT快速迭代重建算法

A Fast Iterative Reconstruction Algorithm of Sparse Angular CT Based on the Selective Total Variation

针对利用稀疏角度投影数据实现优质CT图像重建的问题,提出了一种改进的基于选择性图像全变差(TV)约束的快速迭代重建算法。该算法采用两相式重建策略,首先利用代数重建算法(ART)重建中间图像并进行非负性约束,然后采用选择性TV最小化对上述图像进行优化修正,两步交替进行直到满足某一收敛准则。为了进一步提升算法效能,该算法在迭代过程中应用快速收敛技术加快算法收敛。应用该算法对仿真的Sheep-Logan体模进行重建,实验结果表明,该算法不仅提高了图像的重建质量,保护了图像的边缘信息,而且显著加快了迭代重建的收敛速度。

Aiming at the problem of high-quality image reconstruction from projection data at sparse angular views, we proposed an improved fast iterative reconstruction algorithm based on the minimization of selective image total variation （TV）. The new reconstruction scheme consists of two components. Firstly, the algebraic reconstruction technique （ART） algorithm was adopted to reconstruct image that met the identity and non-negativity of projection data, and then, secondly, the selective TV minimization was used to modify the above image. Two phases were al- ternated until it met the convergence criteria. In order to further speed up the convergence of the algorithm, we ap- plied a fast convergence technology in the iterative process. Experiments on simulated Sheep-Logan phantom were carried out. The results demonstrated that the new method not only improved image reconstruction quality and pro- tected the edge of the image characteristics, but also improvedthe convergence speed of the iterative reconstruction significantly.