Inversion of Spherical Means and the Wave Equation in Even Dimensions. - Markus Haltmeier; David Finch; Rakesh (SIAM J. Appl. Math., 2007)

On Steepest-Descent-Kaczmarz methods for regularizing systems of nonlinear ill-posed equations. - A. De Cezaro; Markus Haltmeier; Antonio Leitão; Otmar Scherzer (Appl. Math. Comput., 2008)

Variational Methods in Imaging. - Otmar Scherzer; Markus Grasmair; Harald Grossauer; Markus Haltmeier; Frank Lenzen (Springer, 2009)

A Reconstruction Algorithm for Photoacoustic Imaging Based on the Nonuniform FFT. - Markus Haltmeier; Otmar Scherzer; Gerhard Zangerl (IEEE Trans. Medical Imaging, 2009)

The residual method for regularizing ill-posed problems. - Markus Grasmair; Markus Haltmeier; Otmar Scherzer (Appl. Math. Comput., 2011)

A Mollification Approach for Inverting the Spherical Mean Radon Transform. - Markus Haltmeier (SIAM J. Appl. Math., 2011)

Inversion Formulas for a Cylindrical Radon Transform. - Markus Haltmeier (SIAM J. Imaging Sci., 2011)

Block-sparse analysis regularization of ill-posed problems via l2, 1-minimization. - Markus Haltmeier (MMAR, 2013)

Inversion of circular means and the wave equation on convex planar domains. - Markus Haltmeier (Comput. Math. Appl., 2013)

Stable Signal Reconstruction via 1 -Minimization in Redundant, Non-Tight Frames. - Markus Haltmeier (IEEE Trans. Signal Process., 2013)

Universal Inversion Formulas for Recovering a Function from Spherical Means. - Markus Haltmeier (SIAM J. Math. Anal., 2014)

A Novel Compressed Sensing Scheme for Photoacoustic Tomography. - Michael Sandbichler; Felix Krahmer; Thomas Berer; Peter Burgholzer; Markus Haltmeier (SIAM J. Appl. Math., 2015)

Recovering a Function from Circular Means or Wave Data on the Boundary of Parabolic Domains. - Markus Haltmeier; Sergiy Pereverzyev Jr. (SIAM J. Imaging Sci., 2015)

Sampling Conditions for the Circular Radon Transform. - Markus Haltmeier (IEEE Trans. Image Process., 2016)

Deep Learning for Photoacoustic Tomography from Sparse Data. - Stephan Antholzer; Markus Haltmeier; Johannes Schwab (CoRR, 2017)

A Framework for Compressive Time-of-Flight 3D Sensing. - Stephan Antholzer; Christoph Wolf; Michael Sandbichler; Markus Dielacher; Markus Haltmeier (CoRR, 2017)

The Radon Transform over Cones with Vertices on the Sphere and Orthogonal Axes. - Daniela Schiefeneder; Markus Haltmeier (SIAM J. Appl. Math., 2017)

Analysis of Iterative Methods in Photoacoustic Tomography with Variable Sound Speed. - Markus Haltmeier; Linh V. Nguyen (SIAM J. Imaging Sci., 2017)

Analytic Inversion of a Conical Radon Transform Arising in Application of Compton Cameras on the Cylinder. - Sunghwan Moon; Markus Haltmeier (SIAM J. Imaging Sci., 2017)

Inversion of the Attenuated V-Line Transform With Vertices on the Circle. - Markus Haltmeier; Sunghwan Moon; Daniela Schiefeneder (IEEE Trans. Computational Imaging, 2017)

A U-Nets Cascade for Sparse View Computed Tomography. - Andreas Kofler; Markus Haltmeier; Christoph Kolbitsch; Marc Kachelrieß; Marc Dewey (MLMIR@MICCAI, 2018)

Image-Based Fashion Product Recommendation with Deep Learning. - Hessel Tuinhof; Clemens Pirker; Markus Haltmeier (LOD, 2018)

NETT: Solving Inverse Problems with Deep Neural Networks. - Housen Li; Johannes Schwab; Stephan Antholzer; Markus Haltmeier (CoRR, 2018)

Stochastic Proximal Gradient Algorithms for Multi-Source Quantitative Photoacoustic Tomography. - Simon Rabanser; Lukas Neumann; Markus Haltmeier (Entropy, 2018)

Analysis of the Linearized Problem of Quantitative Photoacoustic Tomography. - Markus Haltmeier; Lukas Neumann; Linh V. Nguyen; Simon Rabanser (SIAM J. Appl. Math., 2018)

The Averaged Kaczmarz Iteration for Solving Inverse Problems. - Housen Li; Markus Haltmeier (SIAM J. Imaging Sci., 2018)

A Galerkin Least Squares Approach for Photoacoustic Tomography. - Johannes Schwab; Sergiy Pereverzyev Jr.; Markus Haltmeier (SIAM J. Numer. Anal., 2018)

Random 2.5D U-net for Fully 3D Segmentation. - Christoph Angermann; Markus Haltmeier (MLMECH/CVII-STENT@MICCAI, 2019)

Operator Learning Approach for the Limited View Problem in Photoacoustic Tomography. - Florian Dreier; Sergiy Pereverzyev Jr.; Markus Haltmeier (Comput. Methods Appl. Math., 2019)

Projection-Based 2.5D U-net Architecture for Fast Volumetric Segmentation. - Christoph Angermann; Markus Haltmeier; Ruth Steiger; Sergiy Pereverzyev Jr.; Elke Ruth Gizewski (CoRR, 2019)

A Joint Deep Learning Approach for Automated Liver and Tumor Segmentation. - Nadja Gruber; Stephan Antholzer; Werner Jaschke; Christian Kremser; Markus Haltmeier (CoRR, 2019)

Sparse 𝓁q-regularization of inverse problems with deep learning. - Markus Haltmeier; Linh V. Nguyen; Daniel Obmann; Johannes Schwab (CoRR, 2019)

Sparse regularization of inverse problems by biorthogonal frame thresholding. - Jürgen Frikel; Markus Haltmeier (CoRR, 2019)

Neural Networks-based Regularization of Large-Scale Inverse Problems in Medical Imaging. - Andreas Kofler; Markus Haltmeier; Tobias Schaeffter; Marc Kachelrieß; Marc Dewey; Christian Wald; Christoph Kolbitsch (CoRR, 2019)

Reconstruction Algorithms for Photoacoustic Tomography in Heterogeneous Damping Media. - Markus Haltmeier; Linh V. Nguyen (J. Math. Imaging Vis., 2019)

Analysis of the Block Coordinate Descent Method for Linear Ill-Posed Problems. - Simon Rabanser; Lukas Neumann; Markus Haltmeier (SIAM J. Imaging Sci., 2019)

Sparse Anett For Solving Inverse Problems With Deep Learning. - Daniel Obmann; Linh V. Nguyen; Johannes Schwab; Markus Haltmeier (ISBI Workshops, 2020)

Deep synthesis regularization of inverse problems. - Daniel Obmann; Johannes Schwab; Markus Haltmeier (CoRR, 2020)

Unsupervised Adaptive Neural Network Regularization for Accelerated Radial Cine MRI. - Andreas Kofler; Marc Dewey; Tobias Schaeffter; Christoph Kolbitsch; Markus Haltmeier (CoRR, 2020)

The conical Radon transform with vertices on triple lines. - Markus Haltmeier; Sunghwan Moon (CoRR, 2020)

Data-consistent neural networks for solving nonlinear inverse problems. - Yoeri E. Boink; Markus Haltmeier; Sean Holman; Johannes Schwab (CoRR, 2020)

Regularization of Inverse Problems by Neural Networks. - Markus Haltmeier; Linh V. Nguyen (CoRR, 2020)

Multi-Scale Factorization of the Wave Equation with Application to Compressed Sensing Photoacoustic Tomography. - Gerhard Zangerl; Markus Haltmeier (CoRR, 2020)

Regularization of Inverse Problems by Filtered Diagonal Frame Decomposition. - Andrea Ebner; Jürgen Frikel; Dirk A. Lorenz; Johannes Schwab; Markus Haltmeier (CoRR, 2020)

PiNet: Deep Structure Learning using Feature Extraction in Trained Projection Space. - Christoph Angermann; Markus Haltmeier (CoRR, 2020)

Regularization of systems of nonlinear ill-posed equations: I. Convergence Analysis. - Markus Haltmeier; A. Leitao; Otmar Scherzer (CoRR, 2020)

Regularization of systems of nonlinear ill-posed equations: II. Applications. - Markus Haltmeier; Richard Kowar; A. Leitao; Otmar Scherzer (CoRR, 2020)

A machine learning framework for customer purchase prediction in the non-contractual setting. - Andrés Martínez; Claudia Schmuck; Sergiy Pereverzyev Jr.; Clemens Pirker; Markus Haltmeier (Eur. J. Oper. Res., 2020)

Big in Japan: Regularizing Networks for Solving Inverse Problems. - Johannes Schwab; Stephan Antholzer; Markus Haltmeier (J. Math. Imaging Vis., 2020)

Explicit Inversion Formulas for the Two-Dimensional Wave Equation from Neumann Traces. - Florian Dreier; Markus Haltmeier (SIAM J. Imaging Sci., 2020)

Combining Reconstruction and Edge Detection in Computed Tomography. - Jürgen Frikel; Simon Göppel; Markus Haltmeier (Bildverarbeitung für die Medizin, 2021)

Deep structure learning using feature extraction in trained projection space. - Christoph Angermann; Markus Haltmeier (Comput. Electr. Eng., 2021)

An End-To-End-Trainable Iterative Network Architecture for Accelerated Radial Multi-Coil 2D Cine MR Image Reconstruction. - Andreas Kofler; Markus Haltmeier; Tobias Schaeffter; Christoph Kolbitsch (CoRR, 2021)

Machine Learning for Nondestructive Wear Assessment in Large Internal Combustion Engines. - Christoph Angermann; Steinbjörn Jónsson; Markus Haltmeier; Adéla Moravová; Christian Laubichler; Constantin Kiesling; Martin Kober; Wolfgang Fimml (CoRR, 2021)

Discretization of Learned NETT Regularization for Solving Inverse Problems. - Stephan Antholzer; Markus Haltmeier (J. Imaging, 2021)

Multiscale Factorization of the Wave Equation with Application to Compressed Sensing Photoacoustic Tomography. - Gerhard Zangerl; Markus Haltmeier (SIAM J. Imaging Sci., 2021)

Recovering the Initial Data of the Wave Equation from Neumann Traces. - Florian Dreier; Markus Haltmeier (SIAM J. Math. Anal., 2021)

Unsupervised Joint Image Transfer and Uncertainty Quantification Using Patch Invariant Networks. - Christoph Angermann; Markus Haltmeier; Ahsan Raza Siyal (ECCV Workshops (8), 2022)

Convolutional Dictionary Learning by End-To-End Training of Iterative Neural Networks. - Andreas Kofler; Christian Wald; Tobias Schaeffter; Markus Haltmeier; Christoph Kolbitsch (EUSIPCO, 2022)

Convolutional Analysis Operator Learning by End-to-End Training of Iterative Neural Networks. - Andreas Kofler; Christian Wald; Tobias Schaeffter; Markus Haltmeier; Christoph Kolbitsch (ISBI, 2022)

A deep learning pipeline for the automated segmentation of posterior limb of internal capsule in preterm neonates. - Nadja Gruber; Malik Galijasevic; Milovan Regodic; Astrid Ellen Grams; Christian M. Siedentopf; Ruth Steiger; Marlene Hammerl; Markus Haltmeier; Elke Ruth Gizewski; Tanja Janjic (Artif. Intell. Medicine, 2022)

Compressed Sensing of Indirect Data. - Andrea Ebner; Markus Haltmeier (CoRR, 2022)

A Joint Variational Multichannel Multiphase Segmentation Framework. - Nadja Gruber; Johannes Schwab; Sébastien Court; Elke Ruth Gizewski; Markus Haltmeier (CoRR, 2022)

Feature reconstruction from incomplete tomographic data without detour. - Simon Göppel; Jürgen Frikel; Markus Haltmeier (CoRR, 2022)

Translation invariant diagonal frame decomposition of inverse problems and their regularization. - Simon Göppel; Jürgen Frikel; Markus Haltmeier (CoRR, 2022)

Analysis for Full-Field Photoacoustic Tomography with Variable Sound Speed. - Linh Nguyen; Markus Haltmeier; Richard Kowar; Ngoc Do (SIAM J. Imaging Sci., 2022)

Variational multichannel multiclass segmentation endgraf using unsupervised lifting with CNNs. - Nadja Gruber; Johannes Schwab; Sébastien Court; Elke Ruth Gizewski; Markus Haltmeier (CoRR, 2023)

Uncertainty-Aware Null Space Networks for Data-Consistent Image Reconstruction. - Christoph Angermann; Simon Göppel; Markus Haltmeier (CoRR, 2023)

A complementary 𝓁1-TV reconstruction algorithm for limited data CT. - Simon Göppel; Jürgen Frikel; Markus Haltmeier (CoRR, 2023)

Translation invariant diagonal frame decomposition for the Radon transform. - Simon Göppel; Jürgen Frikel; Markus Haltmeier (CoRR, 2023)

Convergence analysis of equilibrium methods for inverse problems. - Daniel Obmann; Markus Haltmeier (CoRR, 2023)

Convergence of non-linear diagonal frame filtering for regularizing inverse problems. - Andrea Ebner; Markus Haltmeier (CoRR, 2023)

Data-proximal null-space networks for inverse problems. - Simon Göppel; Jürgen Frikel; Markus Haltmeier (CoRR, 2023)

Single-Image based unsupervised joint segmentation and denoising. - Nadja Gruber; Johannes Schwab; Noémie Debroux; Nicolas Papadakis; Markus Haltmeier (CoRR, 2023)

Superiorized Regularization of Inverse Problems. - Aviv Gibali; Markus Haltmeier (CoRR, 2023)

Relaxed data-consistency for limited bandwidth photoacoustic tomography. - Daniel Obmann; Markus Haltmeier (CoRR, 2023)

Sampling and resolution in sparse view photoacoustic tomography. - Markus Haltmeier; Daniel Obmann; Karoline Felbermayer; Florian Hinterleitner; Peter Burgholzer (CoRR, 2023)

Heat diffusion blurs photothermal images with increasing depth. - Peter Burgholzer; Günther Mayr; Gregor Thummerer; Markus Haltmeier (CoRR, 2023)

Breaking the Resolution limit in Photoacoustic Imaging using Positivity and Sparsity. - Peter Burgholzer; Johannes Bauer-Marschallinger; Mike Hettich; Markus Haltmeier (CoRR, 2023)

Data-driven Morozov regularization of inverse problems. - Markus Haltmeier; Richard Kowar; Markus Tiefenthaler (CoRR, 2023)

Three-dimensional Bone Image Synthesis with Generative Adversarial Networks. - Christoph Angermann; Johannes Bereiter-Payr; Kerstin Stock; Markus Haltmeier; Gerald Degenhart (CoRR, 2023)

Surface topography characterization using a simple optical device and artificial neural networks. - Christoph Angermann; Markus Haltmeier; Christian Laubichler; Steinbjörn Jónsson; Matthias Schwab; Adéla Moravová; Constantin Kiesling; Martin Kober; Wolfgang Fimml (Eng. Appl. Artif. Intell., 2023)

Unsupervised single-shot depth estimation using perceptual reconstruction. - Christoph Angermann; Matthias Schwab; Markus Haltmeier; Christian Laubichler; Steinbjörn Jónsson (Mach. Vis. Appl., 2023)

Correction: Unsupervised single-shot depth estimation using perceptual reconstruction. - Christoph Angermann; Matthias Schwab; Markus Haltmeier; Christian Laubichler; Steinbjörn Jónsson (Mach. Vis. Appl., 2023)

SIRU-Net : Smoothing Inception Residual U-Net for Deformable Medical Image Registration. - Ahsan Raza Siyal; Astrid Ellen Grams; Markus Haltmeier (BIBM, 2024)

Beyond the Standards: Fully-Automated Aortic Annulus Segmentation on Contrast-Free Magnetic Resonance Imaging Using a Computational Aorta Unwrapping Method. - Enrique Almar-Munoz; Mathias Pamminger; Christian Kremser; Markus Haltmeier; Agnes Mayr (CMRxRecon/MBAS/STACOM@MICCAI, 2024)

Multi-loss 3D Segmentation for Enhanced Bi-atrial Segmentation. - Enrique Almar-Munoz; Markus Tiefenthaler; Nohemí Sofia León Contreras; Adria Aguilar-Minguez; Christian Kremser; Markus Haltmeier; Agnes Mayr (CMRxRecon/MBAS/STACOM@MICCAI, 2024)

ENGinnSAND: A Reference Dataset for Monocular Depth Prediction of Line Structures. - Hubert Bottesch; Christoph Angermann; Christian Laubichler; Constantin Kiesling; Markus Haltmeier (LOD (2), 2024)

Deep Gaussian Mixture Model for Unsupervised Image Segmentation. - Matthias Schwab; Agnes Mayr; Markus Haltmeier (LOD (2), 2024)

A Lightweight Residual Network for Unsupervised Deformable Image Registration. - Ahsan Raza Siyal; Astrid Ellen Grams; Markus Haltmeier (IEEE Access, 2024)

Convergence rates for critical point regularization. - Daniel Obmann; Markus Haltmeier (Appl. Math. Comput., 2024)

ECALL: Expectation-calibrated learning for unsupervised blind deconvolution. - Markus Haltmeier; Gyeongha Hwang (CoRR, 2024)

Design, Implementation and Analysis of a Compressed Sensing Photoacoustic Projection Imaging System. - Markus Haltmeier; Matthias Ye; Karoline Felbermayer; Florian Hinterleitner; Peter Burgholzer (CoRR, 2024)

Full Field Inversion of the Attenuated Wave Equation: Theory and Numerical Inversion. - Ngoc Do; Markus Haltmeier; Richard Kowar; Linh V. Nguyen; Robert Nuster (CoRR, 2024)

Error Estimates for Data-driven Weakly Convex Frame-based Image Regularization. - Andrea Ebner; Matthias Schwab; Markus Haltmeier (CoRR, 2024)

Plug-and-Play Image Reconstruction Is a Convergent Regularization Method. - Andrea Ebner; Markus Haltmeier (IEEE Trans. Image Process., 2024)

Lifting-based variational multiclass segmentation algorithm: Design, convergence analysis, and implementation with applications in medical imaging. - Nadja Gruber; Johannes Schwab; Sébastien Court; Elke Ruth Gizewski; Markus Haltmeier (J. Comput. Appl. Math., 2024)

Derivative-Free Iterative One-Step Reconstruction for Multispectral CT. - Thomas Prohaszka; Lukas Neumann; Markus Haltmeier (J. Imaging, 2024)

Data-proximal Neural Networks for Limited-view CT. - Simon Göppel; Jürgen Frikel; Markus Haltmeier (Bildverarbeitung für die Medizin, 2025)

Noisier2Inverse: Self-Supervised Learning for Image Reconstruction With Correlated Noise. - Nadja Gruber; Johannes Schwab; Markus Haltmeier; Ander Biguri; Clemens Dlaska; Gyeongha Hwang (IEEE Access, 2025)

Inversion formulas for the attenuated conical Radon transform: Plane and cylinder case. - Sunghwan Moon; Markus Haltmeier (Appl. Math. Comput., 2025)

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; Daniel Obmann; Markus Haltmeier; Agnes Mayr (Medical Image Anal., 2025)

Error Estimates for Weakly Convex Frame-Based Regularization Including Learned Filters. - Andrea Ebner; Matthias Schwab; Markus Haltmeier (SIAM J. Imaging Sci., 2025)