3 papers
cs.CV2026
CLEAR: Complex Learned Explicit Analytical Regularization for Ultra-Accelerated 4D Flow CMR Reconstruction
German Shâma Wache, Sebastian Neumayer
While compressed-sensing regularizers enable interpretable reconstruction of 4D Flow CMR through transparent variational objectives, their hand-crafted nature is too restrictive un…
cs.CV2026
Weakly Convex Ridge Regularization for 3D Non-Cartesian MRI Reconstruction
German Shâma Wache, Chaithya G R, Asma Tanabene +1
While highly accelerated non-Cartesian acquisition protocols significantly reduce scan time, they often entail long reconstruction delays. Deep learning based reconstruction method…
cs.LG2025
Learning Regularization Functionals for Inverse Problems: A Comparative Study
Johannes Hertrich, Hok Shing Wong, Alexander Denker +16
In recent years, a variety of learned regularization frameworks for solving inverse problems in imaging have emerged. These offer flexible modeling together with mathematical insig…