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.
Original language | English (US) |
---|---|
Title of host publication | 2011 8th IEEE International Symposium on Biomedical Imaging |
Subtitle of host publication | From Nano to Macro, ISBI'11 |
Pages | 1593-1596 |
Number of pages | 4 |
DOIs | |
State | Published - 2011 |
Event | 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 - Chicago, IL, United States Duration: Mar 30 2011 → Apr 2 2011 |
Other
Other | 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11 |
---|---|
Country/Territory | United States |
City | Chicago, IL |
Period | 3/30/11 → 4/2/11 |
Keywords
- Dynamic MRI
- Half-quadratic Regularization
- Low-rank Matrices
- Partial Separability
- Sparsity
- Total Variation
ASJC Scopus subject areas
- Biomedical Engineering
- Radiology Nuclear Medicine and imaging