Keywords: Body, Machine Learning/Artificial IntelligenceMotion 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.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords