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."
Department of Mathematical Sciences Faculty Presentations.
Presentation 318.
https://digitalcommons.georgiasouthern.edu/math-sci-facpres/318
