Sfoglia per Autore CALIMERI, Francesco
Using CNNs for Designing and Implementing an Automatic Vascular Segmentation Method of Biomedical Images
2018-01-01 Bruno, P.; Zaffino, P.; Scaramuzzino, S.; De Rosa, S.; Indolfi, C.; Calimeri, F.; Spadea, M. F.
Segmentation of vessel tree from cine-angiography images for intraoperative clinical evaluation
2018-01-01 Bruno, P.; Zaffino, P.; Scaramuzzino, S.; De Rosa, S.; Indolfi, C.; Calimeri, F.; Spadea, M. F.
Evaluating the Impact of Training Loss on MR to Synthetic CT Conversion
2020-01-01 Sherwani, M. K.; Zaffino, P.; Bruno, P.; Spadea, M. F.; Calimeri, F.
An open-source covid-19 ct dataset with automatic lung tissue classification for radiomics
2021-01-01 Zaffino, P.; Marzullo, A.; Moccia, S.; Calimeri, F.; De Momi, E.; Bertucci, B.; Arcuri, P. P.; Spadea, M. F.
Editorial: Hot topic: Reducing operating times and complication rates through robot-assisted surgery
2022-01-01 Cafolla, D.; Calimeri, F.; Cao, H.; Russo, M.; Sappey-Marinier, D.; Zaffino, P.
Assessing vascular complexity of PAOD patients by deep learning-based segmentation and fractal dimension
2022-01-01 Bruno, P.; Spadea, M. F.; Scaramuzzino, S.; De Rosa, S.; Indolfi, C.; Gargiulo, G.; Giugliano, G.; Esposito, G.; Calimeri, F.; Zaffino, P.
Radiomics-Based Machine Learning Model for Predicting Overall and Progression-Free Survival in Rare Cancer: A Case Study for Primary CNS Lymphoma Patients
2023-01-01 Destito, M.; Marzullo, A.; Leone, R.; Zaffino, P.; Steffanoni, S.; Erbella, F.; Calimeri, F.; Anzalone, N.; De Momi, E.; Ferreri, A. J. M.; Calimeri, T.; Spadea, M. F.
| Titolo | Data di pubblicazione | Autore(i) | File |
|---|---|---|---|
| Using CNNs for Designing and Implementing an Automatic Vascular Segmentation Method of Biomedical Images | 1-gen-2018 | Bruno, P.; Zaffino, P.; Scaramuzzino, S.; De Rosa, S.; Indolfi, C.; Calimeri, F.; Spadea, M. F. | |
| Segmentation of vessel tree from cine-angiography images for intraoperative clinical evaluation | 1-gen-2018 | Bruno, P.; Zaffino, P.; Scaramuzzino, S.; De Rosa, S.; Indolfi, C.; Calimeri, F.; Spadea, M. F. | |
| Evaluating the Impact of Training Loss on MR to Synthetic CT Conversion | 1-gen-2020 | Sherwani, M. K.; Zaffino, P.; Bruno, P.; Spadea, M. F.; Calimeri, F. | |
| An open-source covid-19 ct dataset with automatic lung tissue classification for radiomics | 1-gen-2021 | Zaffino, P.; Marzullo, A.; Moccia, S.; Calimeri, F.; De Momi, E.; Bertucci, B.; Arcuri, P. P.; Spadea, M. F. | |
| Editorial: Hot topic: Reducing operating times and complication rates through robot-assisted surgery | 1-gen-2022 | Cafolla, D.; Calimeri, F.; Cao, H.; Russo, M.; Sappey-Marinier, D.; Zaffino, P. | |
| Assessing vascular complexity of PAOD patients by deep learning-based segmentation and fractal dimension | 1-gen-2022 | Bruno, P.; Spadea, M. F.; Scaramuzzino, S.; De Rosa, S.; Indolfi, C.; Gargiulo, G.; Giugliano, G.; Esposito, G.; Calimeri, F.; Zaffino, P. | |
| Radiomics-Based Machine Learning Model for Predicting Overall and Progression-Free Survival in Rare Cancer: A Case Study for Primary CNS Lymphoma Patients | 1-gen-2023 | Destito, M.; Marzullo, A.; Leone, R.; Zaffino, P.; Steffanoni, S.; Erbella, F.; Calimeri, F.; Anzalone, N.; De Momi, E.; Ferreri, A. J. M.; Calimeri, T.; Spadea, M. F. |
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