Nr 103 Design, Implementation and Analysis of a Compressed Sensing Photoacoustic Projection Imaging System M. Haltmeier, M. Ye, K. Felbermayer, F. Hinterleitner, P. Burgholzer [Download PDF][arxiv.org]
Nr 102 Derivative-Free iterative One-Step Reconstruction for Multispectral CT L. Neumann, M. Haltmeier [Download PDF][arxiv.org]
Nr 101 ECALL: Expectation-calibrated learning for unsupervised blind deconvolution M. Haltmeier, G. Hwang [Download PDF][arxiv.org]
Nr 100 Three-dimensional Bone Image Synthesis with Generative Adversarial Networks C. Angermann , J. Bereiter-Payra, K. Stock , M. Haltmeier, G. Degenhart [Download PDF][arxiv.org]
Nr 99 Data-driven Morozov regularization of inverse problems M. Haltmeier, R. Kowar, M. Tiefentaler [Download PDF][arxiv.org]
Nr 98 Data-proximal null-space networks for inverse problems S. Göppel, J. Frikel, M. Haltmeier [Download PDF][arxiv.org]
Nr 97 Convergence of non-linear diagonal frame filtering for regularizing inverse problems A. Ebner, M. Haltmeier [Download PDF][arxiv.org]
Nr 96 Convergence analysis of equilibrium methods for inverse problems D. Obmann, M. Haltmeier [Download PDF][arxiv.org]
Nr 95 Translation invariant diagonal frame decomposition for the Radon transform S. Göppel, J. Frikel, M. Haltmeier [Download PDF][arxiv.org]
Nr 94 A complementary ℓ1-TV reconstruction algorithm for limited data CT S. Göppel, J. Frikel, M. Haltmeier [Download PDF][arxiv.org]
Nr 93 Uncertainty-Aware Null Space Networks for Data-Consistent Image Reconstruction C. Angermann, S. Göppel, M. Haltmeier [Download PDF][arxiv.org]
Nr 92 Convergence rates for critical point regularization D. Obmann, M. Haltmeier [Download PDF][arxiv.org]
Nr 91 Plug-and-Play image reconstruction is a convergent regularization method A. Ebner, M. Haltmeier [Download PDF][arxiv.org]
Nr 90 Translation invariant diagonal frame decomposition of inverse problems and their regularization S. Göppel, J.Frickel, M. Haltmeier [Download PDF][arxiv.org]
Nr 89 Convergence analysis of critical point regularization with non-convex regularizers D. Obmann, M. Haltmeier [Download PDF][arxiv.org]
Nr 88 Unsupervised Joint Image Transfer and Uncertainty Quantifcation using Patch Invariant Networks C. Angermann, M. Haltmeier, A. R. Siyal [Download PDF][arxiv.org]
Nr 87 Convolutional Dictionary Learning by End-To-End Training of Iterative Neural Networks A. Kofler, C. Wald, T. Schaeffter, M. Haltmeier, C. Kolbitsch [Download PDF][arxiv.org]
Nr 86 Convergence rates for the joint solution of inverse problems with compressed sensing data A. Ebner, M. Haltmeier [Download PDF][arxiv.org]
Nr 85 A Joint Variational Multichannel Multiphase Segmentation Framework N. Gruber, J. Schwab, S. Court, E. Gizewski, M. Haltmeier [Download PDF][arxiv.org]
Nr 84 Feature reconstruction from incomplete tomographic data without detour S. Göppel, J. Frikel, M. Haltmeier [Download PDF][arxiv.org]
Nr 83 Convolutional Analysis Operator Learning by End-To-End Training of Iterative Neural Networks A. Kofler, C. Wald, T. Schaeffter, M. Haltmeier, C. Kolbitsch [Download PDF][arxiv.org]
Nr 82 A Variational View on Statistical Multiscale Estimation M. Haltmeier, H. Li, A. Munk [Download PDF][arxiv.org]
Nr 81 Combining reconstruction and edge detection in computed tomography J. Firkel, S. Göppel, M. Haltmeier [Download PDF][arxiv.org]
Nr 80 An End-Eo-End-Trainable Iterative Network Architecture for Accelerated Radial Multi-Coil 2D Cine MR Reconstruction A. Kofler, M. Haltmeier, T. Schaeffer, C. Kolbitsch [Download PDF][arxiv.org]
Nr 79 Deep Structure Learning using Feature Extraction in Trained Projection Space C.Angerman, M. Haltmeier [Download PDF][arxiv.org]
Nr 78 Augmented NETT regularization of inverse problems S. Antholzer, M.Haltmeier [Download PDF][arxiv.org]
Nr 77 Discretization of learned NETT regularization for solving problems S. Antholzer, M. Haltmeier [Download PDF][arxiv.org]
Nr 76 Regularization of Inverse Problems by Filtered Diagonal Frame Decomposition A. Ebner, J. Frikel, D. Lorenz, J. Schwab, M. Haltmeier [Download PDF][arxiv.org]
Nr 75 Photoacoustic Inversion Formulas Using Mixed Data On Finite Time Intervals F. Dreier, M. Haltmeier [Download PDF][arxiv.org]
Nr 74 Recovering the Initial Data of the Wave Equation from Neumann Traces F. Dreier, M. Haltmeier [Download PDF][arxiv.org]
Nr. 73 Deep synthesis regularization of inverse problems D. Obman, J. Schwab, M. Haltmeier [Download PDF][arxiv.org]
Nr. 72 Multi-Scale factorization of the wave equation with application to compressed sensing photoacoustic tomography G. Zangerl, M. Haltmeier [Download PDF][arxiv.org]
Nr. 71 Regularization of inverse problems by neural networks M. Haltmeier, L.V. Nguyen [Download PDF][arxiv.org]
Nr. 70 Sparse aNETT for solving inverse problems with deep learning D. Obmann, L. Nguyen, J. Schwab, M. Haltmeier [Download PDF ][arxiv.org]
Nr. 69 The conical radon transform with vertices on triple lines M. Haltmeier, S. Moon [Download PDF ][arxiv.org]
Nr. 68 Unsupervised adaptive neural network regularization for accelerated radial cine MRI A. Kofler, M. Dewey, T. Schaeffter, C. Kolbitsch, M. Haltmeier [Download PDF ][arxiv.org]
Nr. 67 Data-consistent neural networks for solving nonlinear inverse problems Y. E. Boink, M. Haltmeier, S. Holman, J. Schwab [Download PDF][arxiv.org]
Nr. 66 Neural networks-based regularization for large-scale medical image reconstruction A. Kofler, M. Haltmeier, T. Schaeffter, M. Kachelriess, M. Dewey, C. Wald, and C. Kolbitsch [Download PDF][arxiv.org]
Nr. 65 Monotonicity of escape probabilities for branching random walks on Zd A. Tzioufas [Download PDF][arxiv.org]
Nr. 64 Sparse regularization of inverse problems by operator-dapted frame thresholding J. Frikel, M. Haltmeier [Download PDF][arxiv.org]
Nr. 63 Projection-Based 2.5D U-net architecture for fast volumetric segmentation C. Angermann, M. Haltmeier, R. Steiger, S. Pereverzyev Jr., E. Gizewski [Download PDF][arxiv.org]
Nr. 62 Explicit inversion formulas for the two-dimensional wave equation from Neuman Traces F. Dreier, M. Haltmeier [Download PDF][arxiv.org]
Nr. 61 Analysis of the block coordinate descent method for linear Ill-Posed problems S. Rabanser, L. Neumann, M. Haltmeier [Download PDF][arxiv.org]
Nr. 60 Sparse synthesis regularization with deep neural networks D. Obmann, J. Schwab, M. Haltmeier [Download PDF][arxiv.org]
Nr. 59 Projection-Based 2.5D U-net architecture for fast volumetric segmentation C. Angermann, M. Haltmeier, R. Steiger, S. Pereverzyev Jr., E. Gizewski [Download PDF][arxiv.org]
Nr. 58 NETT regularization for compressed sensing photoacoustic tomography S. Antholzer, J. Schwab, J.Bauer-Marschallinger, P. Burgholzer, M. Haltmeier [Download PDF][arxiv.org]
Nr. 57 Deep learning versus -minimization for compressed sensing photoacoustic tomography S. Antholzer, J. Schwab, M. Haltmeier [Download PDF][arxiv.org]
Nr. 56 Photoacoustic tomography with direction dependent data: An exact series reconstruction approach G. Zangerl, S. Moon, M. Haltmeier [Download PDF][arxiv.org]
Nr. 55 Big in Japan: Regularizing networks for solving inverse problems J. Schwab, S. Antholzer, M. Haltmeier [Download PDF][arxiv.org]
Nr. 54 Variational regularization of the weighted conical Radon transform M. Haltmeier, D. Schiefeneder [Download PDF ][arxiv.org]
Nr. 53 Full field inversion in photoacoustic tomography with variable sound speed G. Zangerl, M. Haltmeier, L. V. Nguyen, R. Nuster [Download PDF ][arxiv.org]
Nr. 52 Image based fashion product recommendation with deep learning H. Tuinhof, C. Pirker, M. Haltmeier [Download PDF ][arxiv.org]
Nr. 51 NETT: Solving inverse problems with deep neural networks H. Li, J. Schwab, S. Antholzer, M. Haltmeier [Download PDF ][arxiv.org]
Nr. 50 Deep null space learning for inverse problems: Convergence analysis and rates J. Schwab, S. Antholzer, M. Haltmeier [Download PDF ][arxiv.org]
Nr. 49 Compressed sensing for multiple excitation magnetorelaxometry imaging M. Haltmeier, G. Zangerl, P. Schier, D. Baumgarten [Dowload PDF ] [arxiv.org]
Nr. 48 Photoacoustic image reconstruction via deep learning S. Antholzer, M. Haltmeier, R. Nuster, J. Schwab [Download PDF ]
Nr. 47 Reconstruction algorithms for photoacoustic tomography in heterogenous damping media L. V. Nguyen, M. Haltmeier [Download PDF ]
Nr. 46 Stochastic proximal gradient algorithms for multi-source quantitative photoacoustic tomography S. Rabanser, L. Neumann, M. Haltmeier [Download PDF ] [arxiv.org]
Nr. 44 A New sparsification and reconstruction strategy for compressed sensing photoacoustic tomography M. Haltmeier, M. Sandbichler, T. Berer, J. Bauer-Marschallinger, P. Burholzer, L. Nguyen [Download PDF ] [arxiv.org]
Nr. 43 A framework for compressive time-of flight 3D sensing S. Antholzer, C. Wolf, M. Sandbichler, M. Dielacher and M. Haltmeier [Download PDF ] [arxiv.org]
Nr. 42 The quasi-optimality criterion in the linear functional strategy S. Kindermann, S. Pereverzyev Jr., A. Pilipenko [Download PDF ] [arxiv.org]
Nr. 41 The averaged Kaczmarz iteration for solving inverse problems H. Li, M. Haltmeier [Download PDF] [arxiv.org]
Nr. 40 Regularized Nyström subsampling in regression and ranking problems under general smoothness assumptions G.L. Myleiko, S. Pereverzyev Jr., S.G. Solodky [Download PDF ]
Nr. 39 On the configuration space of planar closed kinematic chains G. Zangerl [Download PDF ]
Nr. 38 Operator learning approach for the limited view problem in photoacoustic tomography F. Dreier, S. Pereverzyev Jr., M. Haltmeier [Download PDF ] [arxiv.org]
Nr. 37 Iterative methods for photoacoustic tomography in attenuating acoustic media M. Haltmeier, R. Kowar, L. V. Nguyen [Download PDF ] [arxiv.org]
Nr. 36 Total variation minimization compressed sensing F. Krahmer, C. Kruschel, M. Sandbichler [Download PDF ] [arxiv.org]
Nr. 35 Sequential learning of analysis operators M. Sandbichler, K. Schnass [Download PDF ] [arxiv.org]
Nr. 34 Dictionary learning from incomplete data V. Naumova, K. Schnass [Download PDF ] [arxiv.org]
Nr. 33 Deep learning for photoacoustic tomography from sparse data S. Antholzer, M. Haltmeier, J. Schwab [Download PDF] [arxiv.org]
Nr. 32 Efficient regularization with wavelet sparsity constraints in PAT J. Frikel, M. Haltmeier [Download PDF ] [arxiv.org]
Nr. 31 Analysis of the linearized problem of quantitative photoacoustic tomography M. Haltmeier, L. Neumann, L. V. Nguyen, S. Rabanser [Download PDF ] [arxiv.org]
Nr. 30 A Galerkin least squares approach for photoacoustic tomography J. Schwab, S. Pereverzyev Jr., M. Haltmeier [Download PDF ] [arxiv.org]
Nr. 29 Iterative methods for photoacoustic tomography with variable sound speed M. Haltmeier, L. V. Nguyen [Download PDF ] [arxiv.org]
Nr. 28 A machine learning framework for customer purchase prediction in the non-contractual setting A. Martínez, C. Schmuck, S. Pereverzyev Jr., C. Pirker, M. Haltmeier [Download PDF ]
Nr. 27 Inversion of the attenuated V-line transform for SPECT with Compton cameras M. Haltmeier, S. Moon, D. Schiefeneder [Download PDF ] [arxiv.org]
Nr. 26 Analytic inversion of a conical Radon transform arising in application of Compton cameras on the cylinder S. Moon, M. Haltmeier [Download PDF ] [arxiv.org]
Nr. 25 The Radon Transform over cones with vertices on the sphere and orthogonal axes D. Schiefeneder, M. Haltmeier [Download PDF ] [arxiv.org]
Nr. 24 Compressed sensing and sparsity in photoacoustic tomography M. Haltmeier, T. Berer, S. Moon and P. Burgholzer [Download PDF ]
Nr. 23 Convergence radius and sample complexity of ITKM algorithms for dictionary learning K. Schnass [Download PDF ]
Nr. 22 Nyström type subsampling analyzed as a regularized projection G. Kriukova, S. Pereverzyev Jr., P. Tkachenko [Download PDF ]
Nr. 21 Sampling conditions for the circular Radon Transform M. Haltmeier [Download PDF ]
Nr. 20 A parameter choice strategy for the inversion of multiple observations C. Gerhards, S. Pereverzyev Jr., P. Tkachenko [Download PDF ]
Nr. 19 Single-stage reconstruction algorithm for quantitative photoacoustic tomography M. Haltmeier, L. Neumann, S. Rabanser [Download PDF ]
Nr. 18 Aggregation of regularized solutions from multiple observation modules J. Chen, S. Pereverzev Jr., Y. Xu [Download PDF ]
Nr. 17 The spherical Radon transform with centers on cylindrical surfaces M. Haltmeier, S. Moon [Download PDF ]
Nr. 16 A novel compressed sensing scheme for photoacoustic tomography M. Sandbichler, F. Krahmer, T. Berer, P. Burgholzer, M. Haltmeier [Download PDF ]
Nr. 15 The universal back-projection formula for spherical means and the wave equation on certain quadric hypersurfaces M. Haltmeier, S. Pereverzyev Jr. [Download PDF]
Nr. 14 Introduction to the mathematics of computed tomography M. Haltmeier, S. Pereverzyev Jr. [Download PDF ]
Nr. 13 Exact reconstruction formula for the spherical mean - Radon Transformation on ellipsoids M. Haltmeier [Download PDF ]
Nr. 12 Recovering a function from circular means or wave data on the boundary of parabolic domains M. Haltmeier, S. Pereverzyev Jr. [Download PDF ]
Nr. 11 Multi-penalty regularization for detecting relevant variables K. Hlavackova-Schindler, V. Naumova, S. Pereverzyev Jr. [Download PDF ]
Nr. 10 On the nonlocality of state and wave equation of Treeby and Cox R. Kowar [Download PDF ]
Nr. 9 Graphical Lasso Granger Method with 2-levels-thresholding for recovering causality networks S. Pereverzyve Jr., K. Hlavackova-Schindler [Download PDF ]
Nr. 8 Exact reconstruction formulas for a Radon transform over cones M. Haltmeier [Download PDF ]
Nr. 7 Time reversal for photoacoustic tomography based on the wave equation of Neuman, Smith and Waag R. Kowar [Download PDF ]
Nr. 6 On time reversal in photoacoustic tomography for tissue similar to water R. Kowar [Download PDF ]
Nr. 5 Aggregated motion estimation for image reconstruction in real-time MRI H. Li, M. Haltmeier, S. Zhang, J. Frahm and A. Munk [Download PDF ]
Nr. 4 Extreme value analysis of empirical frame coefficients and implications for densoring by soft-thresholding M. Haltmeier, A. Munk [Download PDF ]
Nr. 3 Universal inversion formulas for recovering a function from spherical means M. Haltmeier [Download PDF ]
Nr. 2 Inversion of circular means and the wave equation on convex planar domains M. Haltmeier [Download PDF ]
Nr.1 Stable signal reconstruction via l1-minimization in redundant, non-tight frames M. Haltmeier [Download PDF ]
][arxiv.org]
] [video-1