Paper Info
Title
Adaptive Weighted Total Variation Minimization Based Alternating Direction Method of Multipliers for Limited Angle CT Reconstruction.
Abstract
In CT image reconstruction, the limited angle problem is an ill-posed problem. To solve this ill-posed problem, the total variation (TV) regularization has been widely used in image reconstruction. In recent years, an algorithm based on TV regularization and alternating direction multiplier method has been proposed and named as ADTVM. ADTVM can reconstruct high-quality images for the limited angle problem. However, ADTVM just considers the homogeneity of image at different directions. In real application, image possesses different properties at different directions. Therefore, we construct an adaptive weighted TV (AwTV) regularization and propose the ADM-AwTV method on the basis of ADTVM. ADM-AwTV is an iterative image reconstruction method which can reveal the anisotropy of image, adaptively. In each iteration, the weights of different directions can update according to the last reconstruction image. Experiments on two simulation images and one real projection data show that the proposed method achieves better reconstruction results than the other iterative image reconstruction methods such as ART-TV and ADTVM for the limited angle problem.
Year
DOI
Venue
2018
10.1109/ACCESS.2018.2873713
IEEE ACCESS
Keywords
Field
DocType
CT image reconstruction,limited angle,alternating direction method of multipliers,adaptive weighted total variation
Iterative reconstruction,Homogeneity (statistics),Anisotropy,Computer science,Algorithm,Multiplier method,Convex function,Total variation minimization,Regularization (mathematics),Compressed sensing,Distributed computing
Journal
Volume
ISSN
Citations 
6
2169-3536
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Fulin Luo1345.85
Weichen Li200.34
Weiping Tu3177.76
Weiwen Wu452.45