| Deep feature learning for knee cartilage segmentation using a triplanar convolutional neural network A Prasoon, K Petersen, C Igel, F Lauze, E Dam, M Nielsen International conference on medical image computing and computer-assisted …, 2013 | 854 | 2013 |
| Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring M Kallenberg, K Petersen, M Nielsen, AY Ng, P Diao, C Igel, CM Vachon, ... IEEE transactions on medical imaging 35 (5), 1322-1331, 2016 | 531 | 2016 |
| Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge EE Bron, M Smits, WM Van Der Flier, H Vrenken, F Barkhof, P Scheltens, ... NeuroImage 111, 562-579, 2015 | 370 | 2015 |
| Gaussian scale-space theory J Sporring, M Nielsen, LM Florack, P Johansen Kluwer Academic Publishers, 1997 | 332* | 1997 |
| Early detection of Alzheimer's disease using M RI hippocampal texture L Sørensen, C Igel, N Liv Hansen, M Osler, M Lauritzen, E Rostrup, ... Human brain mapping 37 (3), 1148-1161, 2016 | 211 | 2016 |
| 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 |
| Eye typing using Markov and active appearance models DW Hansen, JP Hansen, M Nielsen, AS Johansen, MB Stegmann Sixth IEEE Workshop on Applications of Computer Vision, 2002.(WACV 2002 …, 2002 | 146 | 2002 |
| Regularization, scale-space, and edge detection filters M Nielsen, L Florack, R Deriche Journal of Mathematical Imaging and Vision 7, 291-307, 1997 | 138 | 1997 |
| Identification of progressors in osteoarthritis by combining biochemical and MRI-based markers EB Dam, M Loog, C Christiansen, I Byrjalsen, J Folkesson, M Nielsen, ... Arthritis research & therapy 11, 1-11, 2009 | 137 | 2009 |
| Manifold valued statistics, exact principal geodesic analysis and the effect of linear approximations S Sommer, F Lauze, S Hauberg, M Nielsen Computer Vision–ECCV 2010: 11th European Conference on Computer Vision …, 2010 | 134 | 2010 |
| 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 | 130 | 2019 |
| Automatic segmentation of high-and low-field knee MRIs using knee image quantification with data from the osteoarthritis initiative EB Dam, M Lillholm, J Marques, M Nielsen Journal of Medical imaging 2 (2), 024001-024001, 2015 | 127 | 2015 |
| Machine learning and deep learning applications in microbiome research R Hernández Medina, S Kutuzova, KN Nielsen, J Johansen, LH Hansen, ... ISME communications 2 (1), 98, 2022 | 119 | 2022 |
| Texture-based analysis of COPD: a data-driven approach L Sorensen, M Nielsen, P Lo, H Ashraf, JH Pedersen, M De Bruijne IEEE transactions on medical imaging 31 (1), 70-78, 2011 | 117 | 2011 |
| Mass preserving image registration for lung CT V Gorbunova, J Sporring, P Lo, M Loeve, HA Tiddens, M Nielsen, ... Medical image analysis 16 (4), 786-795, 2012 | 101 | 2012 |
| An artificial intelligence–based mammography screening protocol for breast cancer: outcome and radiologist workload AD Lauritzen, A Rodríguez-Ruiz, MC von Euler-Chelpin, E Lynge, ... Radiology 304 (1), 41-49, 2022 | 100 | 2022 |
| The intrinsic structure of optic flow incorporating measurement duality L Florack, W Niessen, M Nielsen International Journal of Computer Vision 27, 263-286, 1998 | 97 | 1998 |
| Ensemble support vector machine classification of dementia using structural MRI and mini-mental state examination L Sørensen, M Nielsen, Alzheimer's Disease Neuroimaging Initiative Journal of neuroscience methods 302, 66-74, 2018 | 96 | 2018 |
| Sensitivity of screening mammography by density and texture: a cohort study from a population-based screening program in Denmark M von Euler-Chelpin, M Lillholm, I Vejborg, M Nielsen, E Lynge Breast Cancer Research 21, 1-7, 2019 | 88 | 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 | 87 | 2021 |
Lauge SørensenFormerly Associated Professor at University of Copenhagen; Head of Development, Cerebriu A/SBestätigte E-Mail-Adresse bei diku.dk
