Search Results for author: Daniel Obmann

Found 5 papers, 0 papers with code

Error correcting 2D-3D cascaded network for myocardial infarct scar segmentation on late gadolinium enhancement cardiac magnetic resonance images

no code implementations26 Jun 2023 Matthias Schwab, Mathias Pamminger, Christian Kremser, Daniel Obmann, Markus Haltmeier, Agnes Mayr

Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) imaging is considered the in vivo reference standard for assessing infarct size (IS) and microvascular obstruction (MVO) in ST-elevation myocardial infarction (STEMI) patients.

Segmentation

Convergence analysis of equilibrium methods for inverse problems

no code implementations2 Jun 2023 Daniel Obmann, Markus Haltmeier

Recently, the use of deep equilibrium methods has emerged as a new approach for solving imaging and other ill-posed inverse problems.

Sparse aNETT for Solving Inverse Problems with Deep Learning

no code implementations20 Apr 2020 Daniel Obmann, Linh Nguyen, Johannes Schwab, Markus Haltmeier

We propose a sparse reconstruction framework (aNETT) for solving inverse problems.

Deep synthesis regularization of inverse problems

no code implementations1 Feb 2020 Daniel Obmann, Johannes Schwab, Markus Haltmeier

For these deep learning methods, however, a solid theoretical foundation in the form of reconstruction guarantees is missing.

Augmented NETT Regularization of Inverse Problems

no code implementations8 Aug 2019 Daniel Obmann, Linh Nguyen, Johannes Schwab, Markus Haltmeier

We propose aNETT (augmented NETwork Tikhonov) regularization as a novel data-driven reconstruction framework for solving inverse problems.

Cannot find the paper you are looking for? You can Submit a new open access paper.