Magnetic Resonance Imaging

Repository to generate synthetic MRI from q*MRI maps with deep learning physics-informed approached as described by Jacobs Luuk et al. Medical Physics 2023 "Generalizable synthetic MRI with physics-informed convolutional networks".

A framework for designing, prototyping, testing and validating MR pulse sequences. Sequences can be designed or imported from Siemens IDEA; sequence timing can be tested, and the sequence can be fed to MRiLab for MR physics simulations.