Name
Abstract | ||
|---|---|---|
An increasing number of X-ray CT procedures are being conducted with drastically reduced dosage, due at least in part to advances in statistical reconstruction methods that can deal more effectively with noise than can traditional techniques. As data become photon-limited, more detailed models are necessary to deal with count rates that drop to the levels of system electronic noise. We present two... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TMI.2016.2606338 | IEEE Transactions on Medical Imaging |
Keywords | Field | DocType |
Photonics,Detectors,Image reconstruction,Computed tomography,Additives,Data models,Estimation | Iterative reconstruction,Photon,Computer vision,Data modeling,Noise (electronics),Artificial intelligence,Detector,Photonics,Mathematics,Bayesian probability,Pointwise | Journal |
Volume | Issue | ISSN |
36 | 1 | 0278-0062 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhiqian Chang | 1 | 2 | 1.10 |
| Ruoqiao Zhang | 2 | 24 | 2.71 |
| Jean-Baptiste Thibault | 3 | 40 | 6.78 |
| Debashish Pal | 4 | 12 | 1.64 |
| Lin Fu | 5 | 2 | 1.07 |
| Ken D. Sauer | 6 | 576 | 90.54 |
| Charles A. Bouman | 7 | 2740 | 473.62 |