An Iterative Algorithm For Solving Underdetermined Linear Systems In Computed Tomography
Document Type
Presentation
Presentation Date
4-20-2013
Abstract or Description
The sparse solutions of an underdetermined linear system Ax = b under certain condition can be obtained by solving a constrained l1-minimization problem: min ||x||1 subject to Ax = b. An generalized l1 greedy algorithm is proposed. It is implemented as a generalized total variation minimization for reconstruction of medical images with sparse gradients in computed tomography. Numerical experiments are also given to illustrate the advantage of the new iterative algorithm.
Sponsorship/Conference/Institution
New Frontiers in Numerical Analysis and Scientific Computing
Location
Kent, OH
Recommended Citation
Li, Xiezhang.
2013.
"An Iterative Algorithm For Solving Underdetermined Linear Systems In Computed Tomography."
Mathematical Sciences: Faculty Presentations.
Presentation 318.
https://digitalcommons.georgiasouthern.edu/math-sci-facpres/318
