PROPELLER based acquisitions have the unique ability to give low resolution images for each echo train acquired and are often used for motion correction. However, motion correction with PROPELLER can often be hindered due to the low resolution nature of each shot. We propose a technique which leverages recent advancements in super resolution neural networks to enhance low resolution PROPELLER shots for better inter-shot motion estimation.
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