2 papers
physics.med-ph2026
Quantitative mapping from conventional MRI using self-supervised physics-guided deep learning: applications to a large-scale, clinically heterogeneous dataset
Jelmer van Lune, Stefano Mandija, Oscar van der Heide +5
Magnetic resonance imaging (MRI) is a cornerstone of clinical neuroimaging, yet conventional MRIs provide qualitative information heavily dependent on scanner hardware and acquisit…
eess.IV2023
Towards retrospective motion correction and reconstruction for clinical 3D brain MRI protocols with a reference contrast
Gabrio Rizzuti, Tim Schakel, Niek R. F. Huttinga +3
Motion artifacts often spoil the radiological interpretation of MR images, and in the most severe cases the scan needs be repeated, with additional costs for the provider. We discu…