Downloads provided by UsageCounts
This is the fully sampled raw dataset used in the MoDL paper acquired using the 3D T2-CUBE sequence at the University of Iowa. Please see the paper for the details. If you use this dataset then please consider citing this paper. Titled : MoDL: Model-Based Deep Learning Architecture for Inverse Problems by H.K. Aggarwal, M.P Mani, and Mathews Jacob in IEEE Transactions on Medical Imaging, 2019 IEEExplore Link: https://ieeexplore.ieee.org/document/8434321 Arxiv paper PDF Link: https://arxiv.org/abs/1712.02862 Python Source code link: https://github.com/hkaggarwal/modl Thank you
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 18 | |
| downloads | 3 |

Views provided by UsageCounts
Downloads provided by UsageCounts