Liu Nan, Huang Jing, Ma Jian-hua, Lu Li-jun, Feng Qian-jin, Chen Wu-fan
Laboratory of Medical Information, School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China.
Nan Fang Yi Ke Da Xue Xue Bao. 2010 Oct;30(10):2224-8.
Based on the fact that nonlocal means (NL-means) filtered image can likely produce an acceptable priori solution, we propose a sparse angular CT projection onto convex set (POCS) reconstruction using NL-means iterative modification. The new reconstruction scheme consists of two components, POCS and NL-means filter. In each phase of the sparse angular CT iterative reconstruction, we first used POCS algorithm to meet the identity and non-negativity of projection data, and then performed NL-means filter to the image obtained by POCS method for image quality improvement. Simulation experiments showed that the proposed POCS scheme can significantly improve the quality of sparse angular CT image by suppressing the noise and removing the streak-artifacts.
基于非局部均值（NL-means）滤波图像可能产生可接受的先验解这一事实，我们提出了一种使用NL-means迭代修正的凸集上的稀疏角CT投影（POCS）重建方法。新的重建方案由两部分组成，即POCS和NL-means滤波器。在稀疏角CT迭代重建的每个阶段，我们首先使用POCS算法来满足投影数据的一致性和非负性，然后对通过POCS方法获得的图像执行NL-means滤波以提高图像质量。模拟实验表明，所提出的POCS方案可以通过抑制噪声和去除条纹伪影来显著提高稀疏角CT图像的质量。
