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Deep Deep Learning With BART (Trained Weights and Example Data)

<p>This repository contains data required to reproduce the figures of the manuscript Deep, Deep Learning with BART. The corresponding scripts can be found at&nbsp;https://github.com/mrirecon/deep-deep-learning-with-bart.</p> <p>The example data in this repository are based on the data published with the manuscripts of the Variational Network [1] and MoDL [2].</p> <p>[1]: Hammernik K, Klatzer T, Kobler E, Recht MP, Sodickson DK, Pock T, Knoll F.<br> Learning a variational network for reconstruction of accelerated MRI data.<br> Magn Reson Med 2018; 79:3055-3071.</p> <p>[2]:&nbsp;Aggarwal HK, Mani MP, Jacob M.<br> MoDL: Model-Based Deep Learning Architecture for Inverse Problems.<br> IEEE Trans Med Imaging 2019; 38:394--405.</p> <p>&nbsp;</p>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
12
Reuse readiness
8
Engagement
8