Accelerated MRI has the potential to significantly improve image quality without increasing costs, especially for low field strengths. A series of undersampled images are averaged for every unique permutation, and their SNR dependency is fitted to the Stretched-Exponential-Model. The proposed method was implemented in proactively undersampled phantom images at low field (0.074T) and in retroactively undersampled human lung images at high field (3T) using the FGRE pulse sequence; in all cases, SNR was significantly improved within the same scan duration compared to a fully-sampled image. Reconstruction artefacts were minimized or completely removed using a convolutional neural network.
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