| Semi-supervised medical image segmentation via learning consistency under transformations G Bortsova, F Dubost, L Hogeweg, I Katramados, M De Bruijne Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 217 | 2019 |
| Gray matter age prediction as a biomarker for risk of dementia J Wang, MJ Knol, A Tiulpin, F Dubost, M de Bruijne, MW Vernooij, ... Proceedings of the National Academy of Sciences 116 (42), 21213-21218, 2019 | 181 | 2019 |
| Weakly supervised object detection with 2D and 3D regression neural networks F Dubost, H Adams, P Yilmaz, G Bortsova, G van Tulder, MA Ikram, ... Medical image analysis 65, 101767, 2020 | 124* | 2020 |
| Enlarged perivascular spaces in brain MRI: automated quantification in four regions F Dubost, P Yilmaz, H Adams, G Bortsova, MA Ikram, W Niessen, ... Neuroimage 185, 534-544, 2019 | 99 | 2019 |
| Self-supervised graph neural networks for improved electroencephalographic seizure analysis S Tang, JA Dunnmon, K Saab, X Zhang, Q Huang, F Dubost, DL Rubin, ... International Conference on Learning Representations, 2021 | 94 | 2021 |
| Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors G Bortsova, C González-Gonzalo, SC Wetstein, F Dubost, I Katramados, ... Medical Image Analysis, 102141, 2021 | 87 | 2021 |
| 3D regression neural network for the quantification of enlarged perivascular spaces in brain MRI F Dubost, H Adams, G Bortsova, MA Ikram, W Niessen, M Vernooij, ... Medical image analysis 51, 89-100, 2019 | 60 | 2019 |
| Comparing methods of detecting and segmenting unruptured intracranial aneurysms on TOF-MRAS: the ADAM challenge KM Timmins, IC van der Schaaf, E Bennink, YM Ruigrok, X An, ... Neuroimage 238, 118216, 2021 | 54 | 2021 |
| Genomics of perivascular space burden unravels early mechanisms of cerebral small vessel disease MG Duperron, MJ Knol, Q Le Grand, TE Evans, A Mishra, A Tsuchida, ... Nature medicine, 1-13, 2023 | 34 | 2023 |
| Deep learning from label proportions for emphysema quantification G Bortsova, F Dubost, S Ørting, I Katramados, L Hogeweg, L Thomsen, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 33 | 2018 |
| Multi-atlas image registration of clinical data with automated quality assessment using ventricle segmentation F Dubost, M de Bruijne, M Nardin, AV Dalca, KL Donahue, AK Giese, ... Medical image analysis 63, 101698, 2020 | 31* | 2020 |
| An end-to-end approach to segmentation in medical images with CNN and posterior-CRF S Chen, ZS Gamechi, F Dubost, G van Tulder, M de Bruijne Medical image analysis 76, 102311, 2022 | 29 | 2022 |
| Automated lesion detection by regressing intensity-based distance with a neural network KMH van Wijnen, F Dubost, P Yilmaz, MA Ikram, WJ Niessen, H Adams, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 24 | 2019 |
| Evaluation and comparison of accurate automated spinal curvature estimation algorithms with spinal anterior-posterior X-Ray images: The AASCE2019 challenge L Wang, C Xie, Y Lin, HY Zhou, K Chen, D Cheng, F Dubost, B Collery, ... Medical image analysis 72, 102115, 2021 | 22 | 2021 |
| DS6, Deformation-aware Semi-supervised Learning: Application to Small Vessel Segmentation with Noisy Training Data S Chatterjee, K Prabhu, M Pattadkal, G Bortsova, F Dubost, H Mattern, ... arXiv preprint arXiv:2006.10802, 2020 | 20* | 2020 |
| Automated estimation of the spinal curvature via spine centerline extraction with ensembles of cascaded neural networks F Dubost, B Collery, A Renaudier, A Roc, N Posocco, W Niessen, ... Computational Methods and Clinical Applications for Spine Imaging: 6th …, 2020 | 19 | 2020 |
| Segmentation of intracranial arterial calcification with deeply supervised residual dropout networks G Bortsova, G van Tulder, F Dubost, T Peng, N Navab, A van der Lugt, ... Medical Image Computing and Computer Assisted Intervention− MICCAI 2017 …, 2017 | 18 | 2017 |
| Determinants of perivascular spaces in the general population: a pooled cohort analysis of individual participant data TE Evans, MJ Knol, P Schwingenschuh, K Wittfeld, S Hilal, MA Ikram, ... Neurology 100 (2), e107-e122, 2023 | 16 | 2023 |
| Hydranet: data augmentation for regression neural networks F Dubost, G Bortsova, H Adams, MA Ikram, W Niessen, M Vernooij, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 15 | 2019 |
| Automated segmentation and volume measurement of intracranial internal carotid artery calcification at noncontrast CT G Bortsova, D Bos, F Dubost, MW Vernooij, MK Ikram, G van Tulder, ... Radiology: Artificial Intelligence 3 (5), e200226, 2021 | 13 | 2021 |
Marleen de BruijneProfessor of AI in Medical Image Analysis; Erasmus MC Rotterdam and University of Copenhagen在 diku.dk 的电子邮件经过验证
