H. Yu and G. Wang, “Compressed Sensing Based Interior Tomography,” Physics in Medicine and Biology, Vol. 54, No. 9, 2009, pp. 2791-2805. doi:10.1088/0031-9155/54/9/014
has been cited by the following article:
TITLE: The Convergence of Two Algorithms for Compressed Sensing Based Tomography
AUTHORS: Xiezhang Li, Jiehua Zhu
KEYWORDS: Compressed Sensing; Image Reconstruction; Total Variation Minimization; Block Iterative Methods
JOURNAL NAME: Advances in Computed Tomography, Vol.1 No.3, December 28, 2012
ABSTRACT: The constrained total variation minimization has been developed successfully for image reconstruction in computed tomography. In this paper, the block component averaging and diagonally-relaxed orthogonal projection methods are proposed to incorporate with the total variation minimization in the compressed sensing framework. The convergence of the algorithms under a certain condition is derived. Examples are given to illustrate their convergence behavior and noise performance.