Optimal noise control in and fast reconstruction of fan-beam computed tomography image.
Optimal noise control in and fast reconstruction of fan-beam computed tomography image.
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DOI：
10.1118/1.598574
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发表时间：
1999-05
期刊：
影响因子：
3.8
通讯作者：
Xiaochuan Pan
中科院分区：
文献类型：
--
作者：
Xiaochuan Pan
我们提出了一种线性的方法，利用统计上互补的信息固有的投影数据的扇形束计算机断层扫描（CT）实现无偏图像方差减少扇形束CT。这种线性的方法导致无限类的混合算法的发展，在扇束CT图像重建。这些混合算法计算效率更高，数值上不太容易受到数据噪声和有限采样的影响比传统的扇束滤波反投影（FFBP）算法。我们还开发了无限类广义扇束滤波反投影（GFFBP）算法，其中包括传统的FFBP算法作为一个特殊的成员。我们从理论上和定量地证明了混合和GFFBP算法是相同的（或不同的）的情况下（或存在）的数据噪声和有限采样的效果。更重要的是，我们确定了统计上最优的混合算法，可能有潜在的显着影响，在扇束CT图像重建。大量的计算机模拟研究的数值结果验证了我们的理论结果。
We proposed a linear approach that exploits statistically complementary information inherent in the projection data of fan-beam computed tomography (CT) for achieving a bias-free image-variance reduction in fan-beam CT. This linear approach leads to the development of infinite classes of hybrid algorithms for image reconstruction in fan-beam CT. These hybrid algorithms are computationally more efficient and numerically less susceptible to data noise and to the effect of finite sampling than the conventional fan-beam filtered back-projection (FFBP) algorithm. We also developed infinite classes of generalized fan-beam filtered back-projection (GFFBP) algorithms, which include the conventional FFBP algorithm as a special member. We demonstrated theoretically and quantitatively that the hybrid and GFFBP algorithms are identical (or different) in the absence (or presence) of data noise and of the effect of finite sampling. More importantly, we identified the statistically optimal hybrid algorithm that may have potentially significant implication to image reconstruction in fan-beam CT. Extensive numerical results of computer-simulation studies validated our theoretical results.