We describe an MRI image synthesis algorithm capable of synthesizing full-head T2w images and FLAIR images.
Our algorithm, REPLICA, is a supervised method and learns the nonlinear intensity mappings for synthesis using innovative features and a multi-resolution design.
We show significant improvement in synthetic image quality over state-of-the-art image synthesis algorithms.
We also demonstrate that image analysis tasks like segmentation perform similarly for real and REPLICA-generated synthetic images.
REPLICA is computationally very fast and can be easily used as a preprocessing tool before further image analysis.