2 papers
physics.med-ph2026
BART Online Open-Source Sequence Toolbox for Computational MRI
Daniel Mackner, Philip Schaten, Markus Huemer +4
Purpose In advanced computational MRI techniques, acquisition and reconstruction techniques are jointly designed. For reproducibility, it is therefore important to provide an open…
physics.med-ph2024
Self-Supervised Learning for Improved Calibrationless Radial MRI with NLINV-Net
Moritz Blumenthal, Chiara Fantinato, Christina Unterberg-Buchwald +3
Purpose: To develop a neural network architecture for improved calibrationless reconstruction of radial data when no ground truth is available for training. Methods: NLINV-Net is a…