A unified framework for upsampling and denoising of diffusion MRI data

Abstract

Diffusion MRI suffers from relatively long scan times and low signal to noise ratio (SNR), which limits the acquired spatial resolution. In this work, we propose a unified framework for denoising and upsampling diffusion datasets based on a sparse representation of the diffusion signal. Our proposed method shows less blurring and increased anatomical details in the pons region when compared to denoising and subsequent spline interpolation. At the junction of the corpus callosum, the corticospinal tract and the cingulum, finer structures are also preserved as evidenced by a high resolution invivo acquisition.