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Abstract #0837

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

Rosie Goodburn1, Movindu Dassanayake2, Bastien Lecoeur1, Prashant Nair1, Uwe Oelfke1, and Andreas Wetscherek1
1Institute of Cancer Research, London, United Kingdom, 2Imperial College London, London, United Kingdom

Synopsis

Keywords: Image Reconstruction, RadiotherapyRespiratory 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.

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Keywords