title: Parameter optimization of relaxed Ordered Subsets Pre-computed Back Projection (BP) based Penalized-Likelihood (OS-PPL) reconstruction in limited-angle X-ray tomography.
abstract: This paper presents a two-step strategy to provide a quality-predictable image reconstruction. A Pre-computed Back Projection based Penalized-Likelihood (PPL) method is proposed in the strategy to generate consistent image quality. To solve PPL efficiently, relaxed Ordered Subsets (OS) is applied. A training sets based evaluation is performed to quantify the effect of the undetermined parameters in OS, which lets the results as consistent as possible with the theoretical one.
authors.affiliation: Department of Electrical and Computer Engineering, Southern Illinois University Carbondale, IL 62901, USA.
authors.forename: Shiyu
authors.initials: S
authors.lastname: Xu
authors.forename: Henri
authors.initials: H
authors.lastname: Schurz
authors.forename: Ying
authors.initials: Y
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D003627:Data Interpretation, Statistical; D016013:Likelihood Functions; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014056:Tomography, X-Ray / Q000295:instrumentation / Q000379:methods*
keywords: Limited angle tomography; Mono-energetic X-ray; Penalized-likelihood; Predictable resolution properties; Relaxed Ordered Subsets; Smoothing parameter