Shi Hongli, Luo Shuqian, Yang Zhi, Wu Geming
School of Biomedical Engineering, Capital Medical University of China, Beijing, China, 100069.
PLoS One. 2015 Sep 29;10(9):e0138498. doi: 10.1371/journal.pone.0138498. eCollection 2015.
The Filtered Back-Projection (FBP) algorithm and its modified versions are the most important techniques for CT (Computerized tomography) reconstruction, however, it may produce aliasing degradation in the reconstructed images due to projection discretization. The general iterative reconstruction (IR) algorithms suffer from their heavy calculation burden and other drawbacks. In this paper, an iterative FBP approach is proposed to reduce the aliasing degradation. In the approach, the image reconstructed by FBP algorithm is treated as the intermediate image and projected along the original projection directions to produce the reprojection data. The difference between the original and reprojection data is filtered by a special digital filter, and then is reconstructed by FBP to produce a correction term. The correction term is added to the intermediate image to update it. This procedure can be performed iteratively to improve the reconstruction performance gradually until certain stopping criterion is satisfied. Some simulations and tests on real data show the proposed approach is better than FBP algorithm or some IR algorithms in term of some general image criteria. The calculation burden is several times that of FBP, which is much less than that of general IR algorithms and acceptable in the most situations. Therefore, the proposed algorithm has the potential applications in practical CT systems.
滤波反投影（FBP）算法及其改进版本是计算机断层扫描（CT）重建中最重要的技术，然而，由于投影离散化，它可能会在重建图像中产生混叠退化。一般的迭代重建（IR）算法存在计算负担重等缺点。本文提出了一种迭代FBP方法来减少混叠退化。在该方法中，将FBP算法重建的图像视为中间图像，并沿原始投影方向进行投影以生成重投影数据。原始数据与重投影数据之间的差异通过特殊的数字滤波器进行滤波，然后通过FBP进行重建以生成校正项。校正项与中间图像相加以对其进行更新。该过程可以迭代执行，以逐渐提高重建性能，直到满足某个停止准则。对实际数据的一些模拟和测试表明，就一些通用图像标准而言，所提出的方法优于FBP算法或一些IR算法。计算负担是FBP的几倍，远小于一般IR算法，并且在大多数情况下是可以接受的。因此，所提出的算法在实际CT系统中具有潜在的应用价值。
