Diffusion MRI

Super resolution reconstruction for quantitative imaging

We developed a super-resolution reconstruction methodology for diffusion and relaxometry MRI. It allows to improved the trade-off between acquisition time, spatial resolution and SNR.

Iterative reweighted linear least squares for the robust estimation of diffusion magnetic resonance parameters

Diffusion weighted magnetic resonance (DW-MR) imaging suffers from physiological noise such as artifacts caused by motion or system instabilities. This obviates the need for robust diffusion parameter estimation techniques. In the past, several techniques have been presented including RESTORE and iRESTORE. However, these techniques are based on nonlinear estimators, and are consequently computationally intensive. We present a new robust, iteratively reweighted linear least squares (IRLLS) estimator.

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