| Whole Brain Vessel Graphs: A Dataset and Benchmark for Graph Learning and Neuroscience Johannes C. Paetzold, Julian McGinnis, Suprosanna Shit, Ivan Ezhov, Paul ... Thirty-fifth Conference on Neural Information Processing Systems Datasets …, 2021 | 29* | 2021 |
| Nisf: Neural implicit segmentation functions N Stolt-Ansó, J McGinnis, J Pan, K Hammernik, D Rueckert International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 7 | 2023 |
| Single-subject multi-contrast MRI super-resolution via implicit neural representations J McGinnis, S Shit, HB Li, V Sideri-Lampretsa, R Graf, M Dannecker, ... International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 6* | 2023 |
| A genetic risk variant for multiple sclerosis severity is associated with brain atrophy C Gasperi, T Wiltgen, J McGinnis, S Cerri, T Moridi, R Ouellette, A Pukaj, ... Annals of Neurology 94 (6), 1080-1085, 2023 | 4 | 2023 |
| LST-AI: A deep learning ensemble for accurate MS lesion segmentation T Wiltgen, J McGinnis, S Schlaeger, F Kofler, CC Voon, A Berthele, ... NeuroImage: Clinical 42, 103611, 2024 | 3 | 2024 |
| Prognostic value of spinal cord lesion measures in early relapsing-remitting multiple sclerosis M Lauerer, J McGinnis, M Bussas, M El Husseini, V Pongratz, C Engl, ... Journal of Neurology, Neurosurgery & Psychiatry 95 (1), 37-43, 2024 | 1 | 2024 |
| SINR: Spline-enhanced implicit neural representation for multi-modal registration V Sideri-Lampretsa, J McGinnis, H Qiu, M Paschali, W Simson, ... Medical Imaging with Deep Learning, 2024 | | 2024 |
| Modeling the acquisition shift between axial and sagittal MRI for diffusion superresolution to enable axial spine segmentation R Graf, H Möller, J McGinnis, S Rühling, M Weihrauch, M Atad, S Shit, ... Medical Imaging with Deep Learning, 0 | | |
Suprosanna ShitUniversity of Zurich | ETH AI Center在 uzh.ch 的电子邮件经过验证
