Gray matter (GM) thickness is a marker of injury and is detected using magnetic resonance imaging (MRI). Even though it possible to acquire images that hassubstantially higher resolution, they suffer from high noise, requiring multiple acquisitions and averaging to yield suitable quality. In this work, we aimed to improve the sensitivity of surface-based GM estimation from 0.5mm resolution MRI acquired over a clinically-normal time. We evaluated four denoising filters and compared the GM thickness estimates using surface reconstruction from the results, showing that it is possible to reduce MRI acquisition time and maintain relevant features for the GM thickness.
This abstract and the presentation materials are available to members only;
a login is required.
