Kati Niinimäki – Sparse X-ray tomography using Bayesian inversion

Carte non disponible

Date/heure
Date(s) - 19/02/2014
14 h 00 min - 15 h 00 min

Catégories Pas de Catégories


“A sparsity promoting reconstruction method is studied in the context of X-ray tomography with limited X-ray projection data. The reconstruction method is based on minimizing a sum of -norm and a -norm. Especially considered is the -norm of wavelet coefficients. Depending on the viewpoint this method can be considered either a) as the inverse problem of finding a Bayesian MAP estimate with Besov space prior or b) as a deterministic regularization with Besov norm penalty.A tailored large-scale primal-dual interior-point method is used to solve the associated constrained minimization problem. The selection of the regularization parameter (or prior parameter, depending on the viewpoint) is performed by a novel technique called the S-curve method. Numerical results are presented both from simulated and from real, experimental data.” http://venda.uef.fi/inverse/FrontPage/People/Kati%20Niinimaki Kati_Niinimäki[

Kati Niinimäki – Sparse X-ray tomography using Bayesian inversion

Carte non disponible

Date/heure
Date(s) - 19/02/2014
14 h 00 min - 15 h 00 min

Catégories Pas de Catégories


“A sparsity promoting reconstruction method is studied in the context of X-ray tomography with limited X-ray projection data. The reconstruction method is based on minimizing a sum of -norm and a -norm. Especially considered is the -norm of wavelet coefficients. Depending on the viewpoint this method can be considered either a) as the inverse problem of finding a Bayesian MAP estimate with Besov space prior or b) as a deterministic regularization with Besov norm penalty.A tailored large-scale primal-dual interior-point method is used to solve the associated constrained minimization problem. The selection of the regularization parameter (or prior parameter, depending on the viewpoint) is performed by a novel technique called the S-curve method. Numerical results are presented both from simulated and from real, experimental data.” http://venda.uef.fi/inverse/FrontPage/People/Kati%20Niinimaki Kati_Niinimäki[