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20142024
most citedExact Reconstruction Formula for the Spherical Mean Radon Transform on Ellipsoids

17 citations · 19 across the 19 of their papers we have counts for

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9 papers · 1 filter

math.NA2024

Error Estimates for Data-driven Weakly Convex Frame-based Image Regularization

Andrea Ebner, Matthias Schwab, Markus Haltmeier

Inverse problems are fundamental in fields like medical imaging, geophysics, and computerized tomography, aiming to recover unknown quantities from observed data. However, these pr…

math.NA2024

Full Field Inversion of the Attenuated Wave Equation: Theory and Numerical Inversion

Ngoc Do, Markus Haltmeier, Richard Kowar +2

Standard photoacoustic tomography (PAT) provides data that consist of time-dependent signals governed by the wave equation, which are measured on an observation surface. In contras…

math.NA2024

Derivative-Free iterative One-Step Reconstruction for Multispectral CT

Thomas Prohaszka, Lukas Neumann, Markus Haltmeier

Image reconstruction in Multispectral Computed Tomography (MSCT) requires solving a challenging nonlinear inverse problem, commonly tackled via iterative optimization algorithms. E…

math.NA2024

ECALL: Expectation-calibrated learning for unsupervised blind deconvolution

Markus Haltmeier, Gyeongha Hwang

Blind deconvolution aims to recover an original image from a blurred version in the case where the blurring kernel is unknown. It has wide applications in diverse fields such as as…

math.NA2023

Breaking the Resolution limit in Photoacoustic Imaging using Positivity and Sparsity

Peter Burgholzer, Johannes Bauer-Marschallinger, Mike Hettich +1

In this tutorial, we aim to directly recreate some of our "aha" moments when exploring the impact of heat diffusion on the spatial resolution limit of photothermal imaging. Our obj…

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…