Name
Abstract | ||
|---|---|---|
For standard laboratory microtomography systems, acquired radiographs do not always adhere to the strict geometrical assumptions of the reconstruction algorithm. The consequence of this geometrical inconsistency is that the reconstructed tomogram contains motion artifacts, e.g., blurring, streaking, double-edges. To achieve a motion-artifact-free tomographic reconstruction, one must estimate, and ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TCI.2018.2811945 | IEEE Transactions on Computational Imaging |
Keywords | Field | DocType |
Radiography,Trajectory,Image reconstruction,Tomography,Geometry,Correlation | Reference frame,Iterative reconstruction,Computer vision,Tomographic reconstruction,Algorithm,Tomography,Reconstruction algorithm,Rate of convergence,Invariant (mathematics),Artificial intelligence,Mathematics,Trajectory | Journal |
Volume | Issue | ISSN |
4 | 2 | 2573-0436 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| S. J. Latham | 1 | 16 | 3.20 |
| Andrew Kingston | 2 | 60 | 8.86 |
| B. Recur | 3 | 12 | 3.16 |
| Glenn R. Myers | 4 | 2 | 1.40 |
| Olaf Delgado Friedrichs | 5 | 6 | 2.62 |
| Adrian P. Sheppard | 6 | 1 | 0.69 |