Name
Abstract | ||
|---|---|---|
Inspired by recent advances in deep learning, we propose a framework for reconstructing dynamic sequences of 2-D cardiac magnetic resonance (MR) images from undersampled data using a deep cascade of convolutional neural networks (CNNs) to accelerate the data acquisition process. In particular, we address the case where data are acquired using aggressive Cartesian undersampling. First, we show that... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TMI.2017.2760978 | IEEE Transactions on Medical Imaging |
Keywords | DocType | Volume |
Image reconstruction,Two dimensional displays,Redundancy,Imaging,Neural networks,Machine learning,Compressed sensing | Journal | 37 |
Issue | ISSN | Citations |
2 | 0278-0062 | 80 |
PageRank | References | Authors |
2.42 | 18 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jo Schlemper | 1 | 180 | 8.11 |
| Jose Caballero | 2 | 663 | 22.59 |
| Jo Hajnal | 3 | 1796 | 119.03 |
| Anthony N Price | 4 | 253 | 15.32 |
| Daniel Rueckert | 5 | 9338 | 637.58 |