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Purpose: To develop an accelerated, robust, and accurate diffusion MRIacquisition and reconstruction technique for submillimeter whole human brainin-vivo scan on a clinical scanner.  Methods: We extend the ultra-high resolution diffusion MRI acquisitiontechnique, gSlider, by allowing under-sampling in q-space and Radio-Frequency(RF)-encoded data, thereby accelerating the total acquisition time ofconventional gSlider. The novel method, termed gSlider-SR, compensates for thelack of acquired information by exploiting redundancy in the dMRI data using abasis of Spherical Ridgelets (SR), while simultaneously enhancing thesignal-to-noise ratio. Using Monte-Carlo simulation with realistic noise levelsand several acquisitions of in-vivo human brain dMRI data (acquired on aSiemens Prisma 3T scanner), we demonstrate the efficacy of our method usingseveral quantitative metrics.  Results: For high-resolution dMRI data with realistic noise levels(synthetically added), we show that gSlider-SR can reconstruct high-qualitydMRI data at different acceleration factors preserving both signal and angularinformation. With in-vivo data, we demonstrate that gSlider-SR can accuratelyreconstruct 860 ${\mu}m$ diffusion MRI data (64 diffusion directions at b =2000 $s/ {mm}^2$), at comparable quality as that obtained with conventionalgSlider with four averages, thereby providing an eight-fold reduction in scantime (from 1 h 20 min to 10 min).  Conclusion: gSlider-SR enables whole-brain high angular resolution dMRI at asubmillimeter spatial resolution with a dramatically reduced acquisition time,making it feasible to use the proposed scheme on existing clinical scanners.

High-fidelity, accelerated whole-brain submillimeter in-vivo diffusion MRI using gSlider-Spherical Ridgelets (gSlider-SR)