Name
Title | ||
|---|---|---|
Further development of image reconstruction from highly undersampled (k, t)-space data with joint partial separability and sparsity constraints |
Abstract | ||
|---|---|---|
Joint use of partial separability (PS) and spatial-spectral sparsity constraints has previously been demonstrated useful for image reconstruction from undersampled data. This paper extends our early work in this area by proposing a new method for jointly enforcing the PS and spatial total variation (TV) constraints for dynamic MR image reconstruction. An algorithm is also described to solve the underlying optimization problem efficiently. The proposed method has been validated using simulated cardiac imaging data, with the expected capability to reduce image artifacts and reconstruction noise. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ISBI.2011.5872707 | ISBI |
Keywords | Field | DocType |
partial separability,image artifacts,optimisation,simulated cardiac imaging data,total variation,dynamic mr image reconstruction algorithm,cardiology,t)-space data,undersampled (k,data analysis,dynamic mri,image reconstruction,optimization,biomedical mri,spatial total variation constraints,low-rank matrices,sparsity constraints,half-quadratic regularization,cardiac mri signals,medical image processing,sparsity,optimization problem,noise,tv,real time systems,magnetic resonance imaging | Iterative reconstruction,Computer vision,Computer science,Cardiac imaging,Artificial intelligence,Dynamic contrast-enhanced MRI,Optimization problem | Conference |
ISSN | ISBN | Citations |
1945-7928 E-ISBN : 978-1-4244-4128-0 | 978-1-4244-4128-0 | 3 |
PageRank | References | Authors |
0.52 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bo Zhao | 1 | 77 | 8.46 |
| Justin P. Haldar | 2 | 350 | 35.40 |
| Anthony G. Christodoulou | 3 | 44 | 6.33 |
| Zhi-Pei Liang | 4 | 522 | 64.94 |