An overview of deep learning in medical imaging focusing on MRI AS Lundervold, A Lundervold Zeitschrift für Medizinische Physik 29 (2), 102-127, 2019 | 2014 | 2019 |
On post-Lie algebras, Lie-Butcher series and moving frames H Munthe-Kaas, A Lundervold Foundations of Computational Mathematics 13 (4), 2013 | 98 | 2013 |
On the Lie enveloping algebra of a post-Lie algebra K Ebrahimi-Fard, A Lundervold, H Munthe-Kaas arXiv preprint arXiv:1410.6350, 2014 | 56 | 2014 |
Automated segmentation of endometrial cancer on MR images using deep learning E Hodneland, JA Dybvik, KS Wagner-Larsen, V Šoltészová, ... Scientific reports 11 (1), 179, 2021 | 40 | 2021 |
A predictive framework based on brain volume trajectories enabling early detection of Alzheimer's disease SA Mofrad, A Lundervold, AS Lundervold, ... Computerized Medical Imaging and Graphics 90, 101910, 2021 | 37 | 2021 |
Cognitive and MRI trajectories for prediction of Alzheimer’s disease SA Mofrad, AJ Lundervold, A Vik, AS Lundervold Scientific reports 11 (1), 2122, 2021 | 37 | 2021 |
Hopf algebras of formal diffeomorphisms and numerical integration on manifolds A Lundervold, H Munthe-Kaas Contemporary Mathematics 539, 295-324, 2011 | 33 | 2011 |
Noncommutative Bell polynomials, quasideterminants and incidence Hopf algebras K Ebrahimi-Fard, A Lundervold, D Manchon International Journal of Algebra and Computation, 2014 | 30 | 2014 |
Algebraic structure of stochastic expansions and efficient simulation K Ebrahimi-Fard, A Lundervold, SJA Malham, H Munthe-Kaas, A Wiese Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2012 | 28 | 2012 |
Post-Lie algebras and isospectral flows K Ebrahimi-Fard, A Lundervold, I Mencattini, HZ Munthe-Kaas SIGMA. Symmetry, Integrability and Geometry: Methods and Applications 11, 093, 2015 | 24 | 2015 |
Predicting conversion to Alzheimer's disease in individuals with Mild Cognitive Impairment using clinically transferable features I Rye, A Vik, M Kocinski, AS Lundervold, AJ Lundervold Scientific Reports 12 (1), 15566, 2022 | 19 | 2022 |
Backward error analysis and the substitution law for Lie group integrators A Lundervold, H Munthe-Kaas Foundations of Computational Mathematics 13 (2), 2013 | 18 | 2013 |
On algebraic structures of numerical integration on vector spaces and manifolds A Lundervold, HZ Munthe-Kaas arXiv preprint arXiv:1112.4465, 2011 | 15 | 2011 |
Fully automatic whole-volume tumor segmentation in cervical cancer E Hodneland, S Kaliyugarasan, KS Wagner-Larsen, N Lura, E Andersen, ... Cancers 14 (10), 2372, 2022 | 14 | 2022 |
Fast semi-supervised segmentation of the kidneys in DCE-MRI using convolutional neural networks and transfer learning AS Lundervold, J Rørvik, A Lundervold 2nd International Scientific Symposium, Functional Renal Imaging: Where …, 2017 | 14 | 2017 |
Pulmonary Nodule Classification in Lung Cancer from 3D Thoracic CT Scans Using fastai and MONAI S Kaliyugarasan, A Lundervold, AS Lundervold International Journal of Interactive Multimedia and Artificial Intelligence …, 2021 | 13 | 2021 |
Association between free-living sleep and memory and attention in healthy adolescents R Stefansdottir, H Gundersen, V Rognvaldsdottir, AS Lundervold, ... Scientific reports 10 (1), 1-13, 2020 | 12 | 2020 |
Synthesizing skin lesion images using CycleGANs – a case study S Fossen-Romsaas, A Storm-Johannessen, AS Lundervold Proceedings of NIK 2020, 2020 | 10 | 2020 |
Does the evaluation stand up to evaluation? A first-principle approach to the evaluation of classifiers K Dyrland, AS Lundervold, PGL Mana arXiv preprint arXiv:2302.12006, 2023 | 5 | 2023 |
2D and 3D U-Nets for skull stripping in a large and heterogeneous set of head MRI using fastai S Kaliyugarasan, M Kocinski, A Lundervold, AS Lundervold Proceedings of NIK 2020, 2020 | 4 | 2020 |