A fast method to emulate an iterative POCS image reconstruction algorithm

作     者：Zeng, Gengsheng L. 

作者机构：Weber State Univ Dept Engn Ogden UT 84408 USA Univ Utah Dept Radiol & Imaging Sci Salt Lake City UT 84108 USA 

出 版 物：《MEDICAL PHYSICS》 (医疗物理学)

年 卷 期：2017年第44卷第10期

页      面：e353-e359页

核心收录：

学科分类：1001[医学-基础医学(可授医学、理学学位)] 1009[医学-特种医学] 10[医学] 

基　　金：NIH [1R01HL108350  U01 EB017185] 

主　　题：edge-enhancing denoising fast algorithms iterative image reconstruction nonlinear filter x ray CT 

摘      要：Purpose: Iterative image reconstruction algorithms are commonly used to optimize an objective function, especially when the objective function is nonquadratic. Generally speaking, the iterative algorithms are computationally inefficient. This paper presents a fast algorithm that has one backprojection and no forward projection. Methods: This paper derives a new method to solve an optimization problem. The nonquadratic constraint, for example, an edge-preserving denoising constraint is implemented as a nonlinear filter. The algorithm is derived based on the POCS (projections onto projections onto convex sets) approach. A windowed FBP (filtered backprojection) algorithm enforces the data fidelity. An iterative procedure, divided into segments, enforces edge-enhancement denoising. Each segment performs nonlinear filtering. Results: The derived iterative algorithm is computationally efficient. It contains only one backprojection and no forward projection. Low-dose CT data are used for algorithm feasibility studies. The nonlinearity is implemented as an edge-enhancing noise-smoothing filter. Conclusions: The patient studies results demonstrate its effectiveness in processing low-dose x ray CT data. This fast algorithm can be used to replace many iterative algorithms. (C) 2017 American Association of Physicists in Medicine