Investigating VoxelMorph Image Registration for Fast 4D Respiratory Compensated Image Reconstruction on an MR-Linac

Respiratory resolved (4D)-MRI is expected to benefit MRI-guided radiotherapy for abdominal-thoracic cancers. However, a current limitation of 4D-MRI is that one has to trade-off between artefacts, spatial-temporal resolution, and spatial coverage. Deformable image registration has been employed to enhance image quality of undersampled 4D-MRIs, but such approaches are usually too slow to be used in MR-guided radiotherapy workflows. We investigated the feasibility of employing models trained using the VoxelMorph framework with a view of leveraging a fast computation to minimise 4D-MRI reconstruction time on the MR-Linac. The models performed well and were ~48 times faster than a common registration method.