Name
Title | ||
|---|---|---|
Recovery Of Parametric Manifold From Reduced Measurements: Application To Magnetic Resonance Parameter Mapping |
Abstract | ||
|---|---|---|
Magnetic resonance (MR) quantitative imaging such as parameter mapping has great potential in clinical applications. It requires acquisition of a sequence of images at different time points to extract the quantitative parameters. A practical challenge is the tradeoff between spatial resolution and acquisition speed. A number of methods have been proposed to address the challenge. In this paper, a novel manifold recovery approach is proposed to obtain the quantitative map from highly reduced measurements. The performance of the proposed method is demonstrated using simulated and real datasets on parameter mapping. |
Year | Venue | Keywords |
|---|---|---|
2015 | 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI) | MR quantitative imaging, parameter mapping, compressed sensing, manifold recovery |
Field | DocType | ISSN |
Iterative reconstruction,Computer vision,Computer science,Parametric statistics,Quantitative imaging,Acceleration,Artificial intelligence,Image resolution,Compressed sensing,Manifold,Magnetic resonance imaging | Conference | 1945-7928 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chao Shi | 1 | 1 | 0.73 |
| Yihang Zhou | 2 | 11 | 3.04 |
| Yanhua Wang | 3 | 47 | 6.35 |
| Jingyuan Lyu | 4 | 17 | 2.83 |
| Dong Liang | 5 | 131 | 14.36 |
| Leslie Ying | 6 | 240 | 29.08 |