3 papers
eess.IV2026
Learning spatially adaptive sparsity level maps for arbitrary convolutional dictionaries
Joshua Schulz, David Schote, Christoph Kolbitsch +2
State-of-the-art learned reconstruction methods often rely on black-box modules that, despite their strong performance, raise questions about their interpretability and robustness.…
eess.IV2025
MRpro - open PyTorch-based MR reconstruction and processing package
Felix Frederik Zimmermann, Patrick Schuenke, Christoph S. Aigner +12
We introduce MRpro, an open-source image reconstruction package built upon PyTorch and open data formats. The framework comprises three main areas. First, it provides unified data…
eess.IV2025
MR imaging in the low-field: Leveraging the power of machine learning
Andreas Kofler, Dongyue Si, David Schote +3
Recent innovations in Magnetic Resonance Imaging (MRI) hardware and software have reignited interest in low-field () and ultra-low-field MRI (). T…