activity
20192023
most citedDeep synthesis regularization of inverse problems

6 citations · 16 across the 7 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

math.NA2023

Sampling and resolution in sparse view photoacoustic tomography

Markus Haltmeier, Daniel Obmann, Karoline Felbermayer +2

We investigate resolution in photoacoustic tomography (PAT). Using Shannon theory, we investigate the theoretical resolution limit of sparse view PAT theoretically, and empirically…

math.NA2023

Relaxed data-consistency for limited bandwidth photoacoustic tomography

Daniel Obmann, Markus Haltmeier

We study the effect of using weaker forms of data-fidelity terms in generalized Tikhonov regularization accounting for model uncertainties. We show that relaxed data-consistency co…

eess.IV2023★ 5 cited

Error correcting 2D-3D cascaded network for myocardial infarct scar segmentation on late gadolinium enhancement cardiac magnetic resonance images

Matthias Schwab, Mathias Pamminger, Christian Kremser +3

Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) imaging is considered the in vivo reference standard for assessing infarct size (IS) and microvascular obstructio…

math.NA2023★ 3 cited

Convergence analysis of equilibrium methods for inverse problems

Daniel Obmann, Gyeongha Hwang, Markus Haltmeier

Solving inverse problems \(Ax = y\) is central to a variety of practically important fields such as medical imaging, remote sensing, and non-destructive testing. The most successfu…

math.OC2023

Convergence rates for critical point regularization

Daniel Obmann, Markus Haltmeier

Tikhonov regularization involves minimizing the combination of a data discrepancy term and a regularizing term, and is the standard approach for solving inverse problems. The use o…