Accelerated MRI using intelligent protocolling and subject-specific denoising

The routine brain screen protocol employed at our institution was accelerated using Look Up Tables to achieve a 1.94x gain in imaging throughput. Image-denoising was performed on accelerated data by leveraging deep learning models trained on contrast-specific publicly available datasets. These were corrupted by native noise during forward modeling. In addition, subject-specific denoising was demonstrated. The superior performance of denoised data on automated volumetry of Alzheimer’s Disease (AD) relevant brain anatomies on T1w data demonstrated potential for accelerated AD imaging.