| The liver tumor segmentation benchmark (lits) P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ... Medical Image Analysis 84, 102680, 2023 | 1274 | 2023 |
| The medical segmentation decathlon M Antonelli, A Reinke, S Bakas, K Farahani, A Kopp-Schneider, ... Nature communications 13 (1), 4128, 2022 | 1003 | 2022 |
| Differential diagnosis of mild cognitive impairment and Alzheimer's disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry L Sørensen, C Igel, A Pai, I Balas, C Anker, M Lillholm, M Nielsen, ... NeuroImage: Clinical 13, 470-482, 2017 | 176 | 2017 |
| Training recurrent neural networks robust to incomplete data: Application to Alzheimer’s disease progression modeling MM Ghazi, M Nielsen, A Pai, MJ Cardoso, M Modat, S Ourselin, ... Medical image analysis 53, 39-46, 2019 | 132 | 2019 |
| One network to segment them all: A general, lightweight system for accurate 3d medical image segmentation M Perslev, EB Dam, A Pai, C Igel Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 109 | 2019 |
| Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients E Jimenez-Solem, TS Petersen, C Hansen, C Hansen, C Lioma, C Igel, ... Scientific reports 11 (1), 3246, 2021 | 88 | 2021 |
| The international workshop on osteoarthritis imaging knee MRI segmentation challenge: a multi-institute evaluation and analysis framework on a standardized dataset AD Desai, F Caliva, C Iriondo, A Mortazi, S Jambawalikar, U Bagci, ... Radiology: Artificial Intelligence 3 (3), e200078, 2021 | 65 | 2021 |
| Lung segmentation from chest X-rays using variational data imputation R Selvan, EB Dam, NS Detlefsen, S Rischel, K Sheng, M Nielsen, A Pai arXiv preprint arXiv:2005.10052, 2020 | 62 | 2020 |
| Deep-learnt classification of light curves A Mahabal, K Sheth, F Gieseke, A Pai, SG Djorgovski, AJ Drake, ... 2017 IEEE symposium series on computational intelligence (SSCI), 1-8, 2017 | 54 | 2017 |
| Multi-domain adaptation in brain MRI through paired consistency and adversarial learning M Orbes-Arteaga, T Varsavsky, CH Sudre, Z Eaton-Rosen, LJ Haddow, ... Domain Adaptation and Representation Transfer and Medical Image Learning …, 2019 | 45 | 2019 |
| Brain region’s relative proximity as marker for Alzheimer’s disease based on structural MRI L Lillemark, L Sørensen, A Pai, EB Dam, M Nielsen, ... BMC medical imaging 14, 1-12, 2014 | 45 | 2014 |
| Uncertainty quantification in medical image segmentation with normalizing flows R Selvan, F Faye, J Middleton, A Pai Machine Learning in Medical Imaging: 11th International Workshop, MLMI 2020 …, 2020 | 37 | 2020 |
| Robust parametric modeling of Alzheimer’s disease progression MM Ghazi, M Nielsen, A Pai, M Modat, MJ Cardoso, S Ourselin, ... Neuroimage 225, 117460, 2021 | 32 | 2021 |
| Knowledge distillation for semi-supervised domain adaptation M Orbes-Arteainst, J Cardoso, L Sørensen, C Igel, S Ourselin, M Modat, ... OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical …, 2019 | 31 | 2019 |
| Domain adaptation and representation transfer and medical image learning with less labels and imperfect data M Orbes-Arteaga, T Varsavsky, CH Sudre, Z Eaton-Rosen, LJ Haddow, ... Springer, 2019 | 30 | 2019 |
| Kernel bundle diffeomorphic image registration using stationary velocity fields and wendland basis functions A Pai, S Sommer, L Sørensen, S Darkner, J Sporring, M Nielsen IEEE transactions on medical imaging 35 (6), 1369-1380, 2015 | 30 | 2015 |
| Robust training of recurrent neural networks to handle missing data for disease progression modeling MM Ghazi, M Nielsen, A Pai, MJ Cardoso, M Modat, S Ourselin, ... arXiv preprint arXiv:1808.05500, 2018 | 27 | 2018 |
| Inflammatory pathway analytes predicting rapid cognitive decline in MCI stage of Alzheimer’s disease JA Pillai, J Bena, G Bebek, LM Bekris, A Bonner‐Jackson, L Kou, A Pai, ... Annals of Clinical and Translational Neurology 7 (7), 1225-1239, 2020 | 23 | 2020 |
| Simultaneous synthesis of FLAIR and segmentation of white matter hypointensities from T1 MRIs M Orbes-Arteaga, MJ Cardoso, L Sørensen, M Modat, S Ourselin, ... arXiv preprint arXiv:1808.06519, 2018 | 23 | 2018 |
| Dementia diagnosis using MRI cortical thickness, shape, texture, and volumetry L Sørensen, A Pai, C Anker, I Balas, M Lillholm, C Igel, M Nielsen Proc MICCAI workshop challenge on computer-aided diagnosis of dementia based …, 2014 | 22 | 2014 |
Mads NielsenProfessor of Computer Science, University of CopenhagenVerified email at diku.edu
