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 | 193 | 308 | ||
| Differentiating kidney stones from phleboliths in unenhanced low-dose computed tomography using radiomics and machine learning | European Radiology |  | 2019 | 294 | 0 | ||
| Metallic artifact reduction by evaluation of the additional value of iterative reconstruction algorithms in hip prosthesis computed tomography imaging | Medicine (Baltimore) | | 2019 | 288 | 229 | ||
| Emphysema quantification using hybrid versus model-based generations of iterative reconstruction: SAFIRE versus ADMIRE | Medicine (Baltimore) | | 2019 | 341 | 198 | ||
| Noninvasive pulmonary nodule characterization using transcutaneous bioconductance: Preliminary results of an observational study | Medicine (Baltimore) | | 2018 | 422 | 300 | ||
| Radiological findings of complications after lung transplantation | Insights into Imaging | | 2018 | 574 | 187 | ||
| Iterative Algorithms Applied to Treated Intracranial Aneurysms | Clinical Neuroradiology | | 2018 | 492 | 1 | ||
| Impact des reconstructions itératives sur la quantification de l'emphysème pulmonaire par CT scanner | | 2017 | 672 | 177 | |||
| Impact of iterative reconstructions on objective and subjective emphysema assessment with computed tomography: a prospective study | European radiology | | 2017 | 553 | 1 |
