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Motion remains a significant challenge in pediatric MRI. Motion-resolved 4D MRI, such as XD-GRASP, is a promising alternative to motion correction. However, long scan times and particularly reconstruction times restricted routine clinical use. This work presents a deep learning approach called MRI-movienet for 4D reconstruction of radial data, which enables acceleration of both acquisition and reconstruction for free-breathing pediatric MRI with only 1 minute scan time and less than 2 seconds reconstruction time. The deep learning approach is demonstrated for free-breathing abdominal pediatric MRI without anesthesia using XD-GRASP as a reference for comparison.
Murray et al. (Wed,) studied this question.