Flores Liubov A, Vidal Vicent, Mayo Patricia, Rodenas Francisco, Verdú Gumersindo
Annu Int Conf IEEE Eng Med Biol Soc. 2013;2013:5143-6. doi: 10.1109/EMBC.2013.6610706.
Although widely used in nuclear medicine (gamma-camera, single photon emission computed tomography (SPECT), positron emission tomography (PET)), iterative reconstruction has not yet penetrated in CT. The main reason for this is that data sets in CT are much larger than in nuclear medicine and iterative reconstruction then becomes computationally very intensive. Graphical Processing Units (GPUs) provide the possibility to reduce effectively the high computational cost of their implementation. It is the goal of this work to develop a GPU-based algorithm to reconstruct high quality images from under sampled and noisy projection data.
尽管迭代重建在核医学（γ相机、单光子发射计算机断层扫描（SPECT）、正电子发射断层扫描（PET））中已被广泛应用，但尚未在CT中普及。主要原因是CT中的数据集比核医学中的大得多，因此迭代重建的计算量变得非常大。图形处理单元（GPU）为有效降低其实现的高计算成本提供了可能性。这项工作的目标是开发一种基于GPU的算法，用于从不完整采样和有噪声的投影数据中重建高质量图像。
