Jake Burnett, Juan Dominguez Duque, Alex Burmester, Jade Guarnera, Karen Caeyenberghs
Assessing the utility of low field MRI in detecting acquired brain injury by employing a paired dataset comprising structural MRI sequences from the low field (64mT) and high-field (3T) MRI scanning systems. We aim to improve the low-field MR images through a novel (artificial intelligence, AI) deep learning approach to generate a synthetic 3T images and examine the ability of these images to maintain diagnostic integrity and the medical information without the introduction of image artefacts. Moreover, we will compare the brain morphometry measurements between the synthetic 3T MRI images and the native 3T MRI images. Our findings will help to fully understand the applicability of low-field MRI for clinical diagnostics, especially in settings where high-field MRI scanners are less accessible.