180 citations · 1.3k across the 95 of their papers we have counts for
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Analysis for Full Field Photoacoustic Tomography with Variable Sound Speed
Linh V. Nguyen, Markus Haltmeier, Richard Kowar +1
Photoacoustic tomography (PAT) is a non-invasive imaging modality that requires recovering the initial data of the wave equation from certain measurements of the solution outside t…
Photoacoustic inversion formulas using mixed data on finite time intervals
Florian Dreier, Markus Haltmeier
We study the inverse source problem in photoacoustic tomography (PAT) for mixed data, which denote a weighted linear combination of the acoustic pressure and its normal derivative…
Combining reconstruction and edge detection in computed tomography
Jürgen Frikel, Simon Göppel, Markus Haltmeier
We present two methods that combine image reconstruction and edge detection in computed tomography (CT) scans. Our first method is as an extension of the prominent filtered backpro…
A Variational View on Statistical Multiscale Estimation
Markus Haltmeier, Housen Li, Axel Munk
We present a unifying view on various statistical estimation techniques including penalization, variational and thresholding methods. These estimators will be analyzed in the conte…
Unpaired Single-Image Depth Synthesis with cycle-consistent Wasserstein GANs
Christoph Angermann, Adéla Moravová, Markus Haltmeier +2
Real-time estimation of actual environment depth is an essential module for various autonomous system tasks such as localization, obstacle detection and pose estimation. During the…
Surface Topography Characterization Using a Simple Optical Device and Artificial Neural Networks
Christoph Angermann, Markus Haltmeier, Christian Laubichler +6
State-of-the-art methods for quantifying wear in cylinder liners of large internal combustion engines require disassembly and cutting of the liner. This is followed by laboratory-b…
An End-To-End-Trainable Iterative Network Architecture for Accelerated Radial Multi-Coil 2D Cine MR Image Reconstruction
Andreas Kofler, Markus Haltmeier, Tobias Schaeffter +1
Purpose: Iterative Convolutional Neural Networks (CNNs) which resemble unrolled learned iterative schemes have shown to consistently deliver state-of-the-art results for image reco…