254 citations · 710 across the 10 of their papers we have counts for
3 papers · 2 filters
Generalizable synthetic MRI with physics-informed convolutional networks
Luuk Jacobs, Stefano Mandija, Hongyan Liu +3
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 acquisitio…
SynthRAD2023 Grand Challenge dataset: generating synthetic CT for radiotherapy
Adrian Thummerer, Erik van der Bijl, Arthur Jr Galapon +6
Purpose: Medical imaging has become increasingly important in diagnosing and treating oncological patients, particularly in radiotherapy. Recent advances in synthetic computed tomo…
Exploring contrast generalisation in deep learning-based brain MRI-to-CT synthesis
Lotte Nijskens, Cornelis, AT van den Berg +2
Background: Synthetic computed tomography (sCT) has been proposed and increasingly clinically adopted to enable magnetic resonance imaging (MRI)-based radiotherapy. Deep learning (…