Improved Low Angular Resolution Diffusion Parametric Maps Using Deep Learning

Motivation: The DTI technique is used to analyze and evaluate the white matter microstructure; however, the acquisition time is too long for clinical practice and large-scale research. Goal(s): To reduce acquisition time by improving the low angular resolution diffusion parametric maps. Approach: The deep-learning framework was used to improve the low angular resolution diffusion parametric maps and image quality measured with PSNR, and NRMSE. Results: Our deep-learning framework improves low angular resolution diffusion parametric maps by effectively acquiring fiber information in FA map and enhancing overall image quality with increased PSNR and decreased NRMSE. Impact: The reduced acquisition time and improved quality of the low angular resolution diffusion parametric maps obtained with our deep-learning framework may benefit to clinicians and researchers who study in white matter microstructure in routine clinical practice and large-scale research.