SM
| Title | Published in | Access level | OA Policy | Year | Views | Downloads | |
|---|---|---|---|---|---|---|---|
| Generative adversarial networks improve the reproducibility and discriminative power of radiomic features | Radiology. Artificial Intelligence | 2020 | 186 | 252 | |||
| Differentiating kidney stones from phleboliths in unenhanced low-dose computed tomography using radiomics and machine learning | European Radiology | 2019 | 283 | 0 | |||
| Metallic artifact reduction by evaluation of the additional value of iterative reconstruction algorithms in hip prosthesis computed tomography imaging | Medicine (Baltimore) | 2019 | 285 | 190 | |||
| Emphysema quantification using hybrid versus model-based generations of iterative reconstruction: SAFIRE versus ADMIRE | Medicine (Baltimore) | 2019 | 337 | 167 | |||
| Noninvasive pulmonary nodule characterization using transcutaneous bioconductance: Preliminary results of an observational study | Medicine (Baltimore) | 2018 | 418 | 228 | |||
| Radiological findings of complications after lung transplantation | Insights into Imaging | 2018 | 570 | 177 | |||
| Iterative Algorithms Applied to Treated Intracranial Aneurysms | Clinical Neuroradiology | 2018 | 480 | 1 | |||
| Impact des reconstructions itératives sur la quantification de l'emphysème pulmonaire par CT scanner | 2017 | 667 | 156 | ||||
| Impact of iterative reconstructions on objective and subjective emphysema assessment with computed tomography: a prospective study | European radiology | 2017 | 546 | 1 |
