Name
Abstract | ||
|---|---|---|
Model-based techniques have the potential to reduce the artifacts and improve resolution in magnetic resonance spectroscopic imaging, without sacrificing the signal-to-noise ratio. However, the current approaches have a few drawbacks that limit their performance in practical applications. Specifically, the classical schemes use less flexible image models that lead to model misfit, thus resulting i... |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/TMI.2007.898583 | IEEE Transactions on Medical Imaging |
Keywords | Field | DocType |
Magnetic resonance,Spectroscopy,Magnetic resonance imaging,Image reconstruction,Image resolution,Signal resolution,Signal to noise ratio,Magnetic fields,Lesions,Image segmentation | Iterative reconstruction,Affine transformation,Linear combination,Computer vision,Segmentation,Biomagnetism,Signal-to-noise ratio,Artificial intelligence,Basis function,Magnetic resonance spectroscopic imaging,Physics | Journal |
Volume | Issue | ISSN |
26 | 10 | 0278-0062 |
Citations | PageRank | References |
10 | 1.03 | 8 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mathews Jacob | 1 | 790 | 59.62 |
| Xiaoping Zhu | 2 | 13 | 2.32 |
| Andreas Ebel | 3 | 12 | 1.59 |
| Norbert Schuff | 4 | 374 | 26.44 |
| Zhi-Pei Liang | 5 | 522 | 64.94 |