21 citations · 25 across the 2 of their papers we have counts for
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cs.LG2023
Rician likelihood loss for quantitative MRI using self-supervised deep learning
Christopher S. Parker, Anna Schroder, Sean C. Epstein +3
Purpose: Previous quantitative MR imaging studies using self-supervised deep learning have reported biased parameter estimates at low SNR. Such systematic errors arise from the cho…
cs.LG2019★ 4 cited
NEURO-DRAM: a 3D recurrent visual attention model for interpretable neuroimaging classification
David Wood, James Cole, Thomas Booth
Deep learning is attracting significant interest in the neuroimaging community as a means to diagnose psychiatric and neurological disorders from structural magnetic resonance imag…