Name
Title | ||
|---|---|---|
3D spatio-temporal analysis for compressive sensing in magnetic resonance imaging of the murine cardiac cycle |
Abstract | ||
|---|---|---|
This paper explores a three-dimensional compressive sensing (CS) technique for reducing measurement time in magnetic resonance imaging (MRI) of the murine (mouse) cardiac cycle. By randomly undersampling a single 2D slice of a mouse heart at regular time intervals as it expands and contracts through the stages of a heartbeat, a CS reconstruction algorithm can be made to exploit transform sparsity in time as well as space. For the purposes of measuring the left ventricular volume in the mouse heart, this 3D approach offers significant advantages against classical 2D spatial compressive sensing. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1117/12.2006591 | Proceedings of SPIE |
Keywords | Field | DocType |
Compressive sensing,MRI,three-dimensional,random sampling,mouse heart | Computer vision,Heartbeat,Mouse Heart,Spatio-Temporal Analysis,Undersampling,Reconstruction algorithm,Artificial intelligence,Cardiac cycle,Compressed sensing,Physics,Magnetic resonance imaging | Conference |
Volume | ISSN | Citations |
8669 | 0277-786X | 0 |
PageRank | References | Authors |
0.34 | 1 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| brice hirst | 1 | 0 | 0.34 |
| Yahong Rosa Zheng | 2 | 885 | 76.15 |
| ming yang | 3 | 0 | 1.01 |
| lixin ma | 4 | 0 | 0.34 |