Data-consistent super resolution for 3D whole-heart MRI using a motion-corrected deep-learning reconstruction framework

Efficient spatial regularisation of dictionary matching using discrete Markov random fields

Joint group sparsity-based motion-compensated deep learning reconstruction for 3D whole-heart joint T1/T2 mapping

Model based rEconstruction by Deep Algorithm unrolLing (MEDAL) for fast 3D whole-heart T2 mapping

Simultaneous 3D T1, T2, and fat-fraction mapping with respiratory-motion correction, for comprehensive liver tissue characterisation at 0.55T