4 papers
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…
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…
NoSENSE: Learned unrolled cardiac MRI reconstruction without explicit sensitivity maps
Felix Frederik Zimmermann, Andreas Kofler
We present a novel learned image reconstruction method for accelerated cardiac MRI with multiple receiver coils based on deep convolutional neural networks (CNNs) and algorithm unr…
PINQI: An End-to-End Physics-Informed Approach to Learned Quantitative MRI Reconstruction
Felix F Zimmermann, Christoph Kolbitsch, Patrick Schuenke +1
Quantitative Magnetic Resonance Imaging (qMRI) enables the reproducible measurement of biophysical parameters in tissue. The challenge lies in solving a nonlinear, ill-posed invers…