Abstract #3348

Super-Resolution Diffusion Imaging using Deep Learning: A Feasibility Study

Nahla M H Elsaid^1,2 and Yu-Chien Wu^1,2

¹Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indiana University, Indianapolis, IN, United States, ²Indiana Alzheimer Disease Center, Indianapolis, IN, United States

In this study, we present and validate the efficacy of using a state-of-the-art deep-learning method to achieve submillimeter high-resolution diffusion-weighted (DW) images. The 2D-based deep-learning method was validated by comparing diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) of the deep-learning high-resolution images and the ground-truth.

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