| Training and deploying a deep learning model for endoscopic severity grading in ulcerative colitis using multicenter clinical trial data BG Becker, F Arcadu, A Thalhammer, CG Serna, O Feehan, F Drawnel, ... Therapeutic advances in gastrointestinal endoscopy 14, 2021 | 369 | 2021 |
| Deep learning algorithm predicts diabetic retinopathy progression in individual patients F Arcadu, F Benmansour, A Maunz, J Willis, Z Haskova, M Prunotto NPJ digital medicine 2 (1), 92, 2019 | 247 | 2019 |
| DDR1 role in fibrosis and its pharmacological targeting MP Solange Moll, Alexis Desmoulière, Marcus J. Moeller, Jean-Claude Pache ... Biochimica et Biophysica Acta (BBA) - Molecular Cell Research, 2019 | 73 | 2019 |
| Deep Learning Predicts OCT Measures of Diabetic Macular Thickening From Color Fundus Photographs F Arcadu, F Benmansour, A Maunz, J Michon, Z Haskova, D McClintock, ... Investigative Ophthalmology & Visual Science 60, 857-60, 2019 | 67 | 2019 |
| Tomographic in vivo microscopy for the study of lung physiology at the alveolar level G Lovric, R Mokso, F Arcadu, I Vogiatzis Oikonomidis, JC Schittny, ... Scientific reports 7 (1), 12545, 2017 | 46 | 2017 |
| Contrast-transfer-function phase retrieval based on compressed sensing P Villanueva-Perez, F Arcadu, P Cloetens, M Stampanoni Optics Letters 42 (6), 1133-1136, 2017 | 19 | 2017 |
| A forward regridding method with minimal oversampling for accurate and efficient iterative tomographic algorithms F Arcadu, M Nilchian, A Studer, M Stampanoni, F Marone IEEE Transactions on Image Processing 25 (3), 1207-1218, 2016 | 13 | 2016 |
| Signal-to-noise criterion for free-propagation imaging techniques at free-electron lasers and synchrotrons P Villanueva-Perez, B Pedrini, R Mokso, M Guizar-Sicairos, F Arcadu, ... Optics Express 24 (4), 3189-3201, 2016 | 12 | 2016 |
| Deep learning automates bidimensional and volumetric tumor burden measurement from MRI in pre-and post-operative glioblastoma patients J Nalepa, K Kotowski, B Machura, S Adamski, O Bozek, B Eksner, ... Computers in biology and medicine 154, 106603, 2023 | 11 | 2023 |
| Author correction: Deep learning algorithm predicts diabetic retinopathy progression in individual patients F Arcadu, F Benmansour, A Maunz, J Willis, Z Haskova, M Prunotto NPJ digital medicine 3 (1), 160, 2020 | 11 | 2020 |
| Imaging samples larger than the field of view: the SLS experience IV Oikonomidis, G Lovric, TP Cremona, F Arcadu, A Patera, JC Schittny, ... Journal of Physics: Conference Series 849 (1), 012004, 2017 | 9 | 2017 |
| On the crucial impact of the coupling projector-backprojector in iterative tomographic reconstruction F Arcadu, M Stampanoni, F Marone arXiv preprint arXiv:1612.05515, 2016 | 9 | 2016 |
| Accuracy of a machine-learning algorithm for detecting and classifying choroidal neovascularization on spectral-domain optical coherence tomography A Maunz, F Benmansour, Y Li, T Albrecht, YP Zhang, F Arcadu, Y Zheng, ... Journal of Personalized Medicine 11 (6), 524, 2021 | 7 | 2021 |
| Deep learning algorithm for patient-level prediction of diabetic retinopathy (DR) response to vascular endothelial growth factor (VEGF) inhibition F Arcadu, F Benmansour, A Maunz, JR Willis, M Prunotto, Z Haskova Investigative Ophthalmology & Visual Science 60 (9), 2806-2806, 2019 | 6 | 2019 |
| Fast iterative reconstruction of data in full interior tomography F Arcadu, F Marone, M Stampanoni Journal of synchrotron radiation 24 (1), 205-219, 2017 | 5 | 2017 |
| Fast gridding projectors for analytical and iterative tomographic reconstruction of differential phase contrast data F Arcadu, M Stampanoni, F Marone Optics Express 24 (13), 14748-14764, 2016 | 4 | 2016 |
| Deep learning algorithm predicts diabetic retinopathy progression in individual patients. NPJ Digit. Med. 2, 92 (2019) F Arcadu, F Benmansour, A Maunz, J Willis, Z Haskova, M Prunotto | 4 | |
| Deep learning algorithm predicts diabetic retinopathy progression in individual patients. npj Digital Medicine. 2019; 2 (1) F Arcadu, F Benmansour, A Maunz, J Willis, Z Haskova, M Prunotto | 3 | 2019 |
| A machine learning approach to predict response to anti-VEGF treatment in patients with neovascular age-related macular degeneration using SD-OCT JN Sahni, A Maunz, F Arcadu, YP Zhang_Schaerer, Y Li, T Albrecht, ... Investigative Ophthalmology & Visual Science 60 (11), PB094-PB094, 2019 | 2 | 2019 |
| Effective segmentation of fresh post-mortem murine lung parenchyma in phase contrast X-ray tomographic microscopy images IV Oikonomidis, TP Cremona, G Lovric, F Arcadu, M Stampanoni, ... Journal of Physics: Conference Series 849 (1), 012006, 2017 | 2 | 2017 |
