3 papers
eess.IV2026
Physics-informed denoising method for image reconstruction in quantitative low-field MRI
Catarina Redshaw Kranich, Claudia Prieto, Christoph Kolbitsch +1
Low-field magnetic resonance imaging (MRI) is becoming increasingly important for medical imaging because it can reduce healthcare costs while ensuring high diagnostic output. Neve…
eess.IV2025
Augment to Augment: Diverse Augmentations Enable Competitive Ultra-Low-Field MRI Enhancement
Felix F Zimmermann
Ultra-low-field (ULF) MRI promises broader accessibility but suffers from low signal-to-noise ratio (SNR), reduced spatial resolution, and contrasts that deviate from high-field st…
eess.IV2025
MRpro: open framework for model-based, learned, and quantitative MR imaging
Felix Frederik Zimmermann, Patrick Schuenke, Christoph S. Aigner +12
We preseent an open-source image reconstruction package built upon PyTorch, enabling modern deep-learning reconstructions. It uses open data formats for input and output (ISMRMRD,…