Name
Abstract | ||
|---|---|---|
In computed tomography, there is a tradeoff between the quality of the reconstructed image and the radiation dose received by the patient. In order to find an appropriate compromise between the image quality of the reconstructed images and the radiation dose, it is important to have reliable methods for evaluating the quality of the reconstructed images. A successful family of methods for the asse... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TMI.2018.2848104 | IEEE Transactions on Medical Imaging |
Keywords | Field | DocType |
Observers,Task analysis,Image quality,Bayes methods,Image reconstruction,Computed tomography,Lesions | Iterative reconstruction,Computer vision,Binary classification,Pattern recognition,Bayes factor,Image quality,Figure of merit,Posterior probability,Artificial intelligence,Covariance matrix,Mathematics,Bayesian probability | Journal |
Volume | Issue | ISSN |
37 | 12 | 0278-0062 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexander Khanin | 1 | 0 | 0.34 |
| Mathias Anton | 2 | 0 | 0.34 |
| Marcel Reginatto | 3 | 0 | 0.34 |
| Clemens Elster | 4 | 96 | 14.27 |