105 citations · 211 across the 13 of their papers we have counts for
15 papers · 1 filter
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…
Regularization of systems of nonlinear ill-posed equations: II. Applications
M. Haltmeier, R. Kowar, A. Leitao +1
In part I we introduced modified Landweber-Kaczmarz methods and have established a convergence analysis. In the present work we investigate three applications: an inverse problem r…
Regularization of systems of nonlinear ill-posed equations: I. Convergence Analysis
M. Haltmeier, A. Leitao, O. Scherzer
In this article we develop and analyze novel iterative regularization techniques for the solution of systems of nonlinear ill--posed operator equations. The basic idea consists in…
Multi-Scale Factorization of the Wave Equation with Application to Compressed Sensing Photoacoustic Tomography
Gerhard Zangerl, Markus Haltmeier
Performing a large number of spatial measurements enables high-resolution photoacoustic imaging without specific prior information. However, the acquisition of spatial measurements…
Regularization of Inverse Problems by Neural Networks
Markus Haltmeier, Linh V. Nguyen
Inverse problems arise in a variety of imaging applications including computed tomography, non-destructive testing, and remote sensing. The characteristic features of inverse probl…
Sparse aNETT for Solving Inverse Problems with Deep Learning
Daniel Obmann, Linh Nguyen, Johannes Schwab +1
We propose a sparse reconstruction framework (aNETT) for solving inverse problems. Opposed to existing sparse reconstruction techniques that are based on linear sparsifying transfo…