An Iterative Algorithm For Solving Underdetermined Linear Systems In Computed Tomography
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.
Institut für Numerische Mathematik und Optimierung Technische Universität Bergakademie
"An Iterative Algorithm For Solving Underdetermined Linear Systems In Computed Tomography."
Mathematical Sciences Faculty Presentations.