An unsupervised deep learning framework is proposed for denoising low-field 64 mT diffusion-weighted MRI images (DWI). The denoised DWI (b-value = 890 s/mm2) and apparent diffusion coefficient (ADC) maps were evaluated in a user study by four expert graders in terms of sharpness, noise reduction, and overall utility. Our framework was found to enable low-field DWI restoration with strong noise while maintaining relevant image features. 62.50% and 64.28% of processed images were rated clearly/far better overall for DWI and ADC, respectively, with only 0.05% of processed DWI and 0% of processed ADC rated clearly/far worse.
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