An algorithm for total variation regularized photoacoustic imaging
Autor(en): | Dong, Yiqiu Gorner, Torsten Kunis, Stefan |
Stichwörter: | EFFICIENT; Fast Fourier transform; INVERSION FORMULAS; Mathematics; Mathematics, Applied; Photoacoustic imaging; RECONSTRUCTION; Spherical mean operator; TOMOGRAPHY; Total variation regularization; TRANSFORM | Erscheinungsdatum: | 2015 | Herausgeber: | SPRINGER | Journal: | ADVANCES IN COMPUTATIONAL MATHEMATICS | Volumen: | 41 | Ausgabe: | 2 | Startseite: | 423 | Seitenende: | 438 | Zusammenfassung: | 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. |
ISSN: | 10197168 | DOI: | 10.1007/s10444-014-9364-1 |
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