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 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]: 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> </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