Search Results for author:
Found 3 papers, 2 papers with code
Generalizable synthetic MRI with physics-informed convolutional networks
In this study, we develop a physics-informed deep learning-based method to synthesize multiple brain magnetic resonance imaging (MRI) contrasts from a single five-minute acquisition and investigate its ability to generalize to arbitrary contrasts to accelerate neuroimaging protocols.
Dictionary-free MR Fingerprinting reconstruction of balanced-GRE sequences
In this work, a method is presented to reconstruct balanced gradient-echo (GRE) acquisitions with established iterative algorithms for nonlinear least-squares, thus bypassing the dictionary computation and the exhaustive search.
Medical Physics
Deep MR to CT Synthesis using Unpaired Data
MR-only radiotherapy treatment planning requires accurate MR-to-CT synthesis.
