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Dong, Y.* ; Görner, T.* ; Kunis, S.

An algorithm for total variation regularized photoacoustic imaging.

Adv. Comput. Math. 41, 423-438 (2015)
Publ. Version/Full Text DOI
Open Access Green as soon as Postprint is submitted to ZB.
Recovery of image data from photoacoustic measurements asks for the inversion of the spherical mean value operator. In contrast to direct inversion methods for specific geometries, we consider a semismooth Newton scheme to solve a total variation regularized least squares problem. During the iteration, each matrix vector multiplication is realized in an efficient way using a recently proposed spectral discretization of the spherical mean value operator. All theoretical results are illustrated by numerical experiments.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Fast Fourier Transform ; Photoacoustic Imaging ; Spherical Mean Operator ; Total Variation Regularization; Mean Radon-transform; Circular Integrating Detectors; Sparse Fourier-transform; Variable Sound Speed; Thermoacoustic Tomography; Spherical Geometry; Inversion Formulas; Newton Method; Reconstruction; Efficient
ISSN (print) / ISBN 1019-7168
e-ISSN 1572-9044
Quellenangaben Volume: 41, Issue: 2, Pages: 423-438 Article Number: , Supplement: ,
Publisher Springer
Publishing Place New York
Reviewing status Peer reviewed