Deep Learning Augmented PROPELLER Reconstruction for Improved MRI Motion Correction

Applying the Periodically Rotated Overlapping Parallel Lines with Enhanced Reconstruction (PROPELLER) technique is one of the strategies to mitigate motion artifacts in MR images. However, due to technical limitations, existing method estimates motion parameters with unsatisfactory results, motion artifacts will still be presented in the final image. Deep learning algorithms are expected to optimize the motion parameter estimation part of PROPELLER technique. We develop a PROPELLER imaging technique incorporating a deep learning model that can provide accurate results and greatly shorten the elapsed time.