IEEE Trans Med Imaging. 2018 Feb;37(2):361-371. doi: 10.1109/TMI.2017.2741781. Epub 2017 Aug 18.
Iterative algorithms have become increasingly popular in computed tomography (CT) image reconstruction, since they better deal with the adverse image artifacts arising from low radiation dose image acquisition. But iterative methods remain computationally expensive. The main cost emerges in the projection and back projection operations, where accurate CT system modeling can greatly improve the quality of the reconstructed image. We present a framework that improves upon one particular aspect-the accurate projection of the image basis functions. It differs from current methods in that it substitutes the high computational complexity associated with accurate voxel projection by a small number of memory operations. Coefficients are computed in advance and stored in look-up tables parameterized by the CT system's projection geometry. The look-up tables only require a few kilobytes of storage and can be efficiently accelerated on the GPU. We demonstrate our framework with both numerical and clinical experiments and compare its performance with the current state-of-the-art scheme-the separable footprint method.
迭代算法在计算机断层扫描 (CT) 图像重建中变得越来越流行，因为它们可以更好地处理由于低辐射剂量图像采集而产生的不良图像伪影。但是迭代方法仍然计算成本很高。主要成本出现在投影和反向投影操作中，在这里，准确的 CT 系统建模可以大大提高重建图像的质量。我们提出了一个框架，改进了一个特定的方面——准确的图像基函数的投影。它与当前的方法不同，它用少量的内存操作替代了与准确体素投影相关的高计算复杂度。系数是预先计算的，并存储在由 CT 系统投影几何参数化的查找表中。查找表只需要几个千字节的存储空间，并且可以在 GPU 上有效地加速。我们用数值和临床实验来演示我们的框架，并将其性能与当前最先进的方案——可分离足迹方法进行比较。
