Robust and Rapid 3D High-Resolution Cranial bone imaging for pediatric patients using MRI

The project proposes four specific aims: 1) develop motion correction to address head motion in unsedated pediatric patients; 2) develop an MR image reconstruction method regularized by a deep-learning prior to reduce MR acquisition time to 1 minute or below; 3) develop a 3D Bayesian neural network to estimate pseudo-CT (pCT) and uncertainty maps from MRI for robust and automated image post-processing; and 4) determine the clinical utility of pCT in identifying cranial fractures and cranial suture patency.