Name
Abstract | ||
|---|---|---|
The reconstruction of dynamic magnetic resonance data from an undersampled k-space has been shown to have a huge potential in accelerating the acquisition process of this imaging modality. With the introduction of compressed sensing (CS) theory, solutions for undersampled data have arisen which reconstruct images consistent with the acquired samples and compliant with a sparsity model in some tran... |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TMI.2014.2301271 | IEEE Transactions on Medical Imaging |
Keywords | Field | DocType |
Dictionaries,Image reconstruction,Transforms,Training,Magnetic resonance imaging,Acceleration,Vectors | Iterative reconstruction,Computer vision,Iterative method,Computer science,Neural coding,Undersampling,Rate of convergence,Artificial intelligence,Acceleration,Compressed sensing,Cartesian coordinate system | Journal |
Volume | Issue | ISSN |
33 | 4 | 0278-0062 |
Citations | PageRank | References |
41 | 1.85 | 19 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jose Caballero | 1 | 663 | 22.59 |
| Anthony N Price | 2 | 253 | 15.32 |
| Daniel Rueckert | 3 | 9338 | 637.58 |
| Jo Hajnal | 4 | 1796 | 119.03 |