| Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer BE Bejnordi, M Veta, PJ Van Diest, B Van Ginneken, N Karssemeijer, ... Jama 318 (22), 2199-2210, 2017 | 1432 | 2017 |
| Breast cancer histopathology image analysis: A review M Veta, JPW Pluim, PJ Van Diest, MA Viergever IEEE transactions on biomedical engineering 61 (5), 1400-1411, 2014 | 495 | 2014 |
| Assessment of algorithms for mitosis detection in breast cancer histopathology images M Veta, PJ Van Diest, SM Willems, H Wang, A Madabhushi, A Cruz-Roa, ... Medical image analysis 20 (1), 237-248, 2015 | 376 | 2015 |
| Automatic nuclei segmentation in H&E stained breast cancer histopathology images M Veta, PJ Van Diest, R Kornegoor, A Huisman, MA Viergever, ... PloS one 8 (7), e70221, 2013 | 312 | 2013 |
| Going fully digital: Perspective of a Dutch academic pathology lab N Stathonikos, M Veta, A Huisman, PJ van Diest Journal of Pathology Informatics, 2013 | 154 | 2013 |
| Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge M Veta, YJ Heng, N Stathonikos, BE Bejnordi, F Beca, T Wollmann, ... Medical image analysis 54, 111-121, 2019 | 127 | 2019 |
| Adversarial training and dilated convolutions for brain MRI segmentation P Moeskops, M Veta, MW Lafarge, KAJ Eppenhof, JPW Pluim Deep learning in medical image analysis and multimodal learning for clinical …, 2017 | 116 | 2017 |
| Marker-controlled watershed segmentation of nuclei in H&E stained breast cancer biopsy images M Veta, A Huisman, MA Viergever, PJ van Diest, JPW Pluim 2011 IEEE international symposium on biomedical imaging: from nano to macro …, 2011 | 96 | 2011 |
| Roto-translation covariant convolutional networks for medical image analysis EJ Bekkers, MW Lafarge, M Veta, KAJ Eppenhof, JPW Pluim, R Duits International conference on medical image computing and computer-assisted …, 2018 | 85 | 2018 |
| Domain-adversarial neural networks to address the appearance variability of histopathology images MW Lafarge, JPW Pluim, KAJ Eppenhof, P Moeskops, M Veta Deep learning in medical image analysis and multimodal learning for clinical …, 2017 | 78 | 2017 |
| Deformable image registration using convolutional neural networks KAJ Eppenhof, MW Lafarge, P Moeskops, M Veta, JPW Pluim Medical Imaging 2018: Image Processing 10574, 105740S, 2018 | 75 | 2018 |
| Mitosis counting in breast cancer: Object-level interobserver agreement and comparison to an automatic method M Veta, PJ Van Diest, M Jiwa, S Al-Janabi, JPW Pluim PloS one 11 (8), e0161286, 2016 | 73 | 2016 |
| Prognostic value of automatically extracted nuclear morphometric features in whole slide images of male breast cancer M Veta, R Kornegoor, A Huisman, AHJ Verschuur-Maes, MA Viergever, ... Modern pathology 25 (12), 1559-1565, 2012 | 67 | 2012 |
| Detecting mitotic figures in breast cancer histopathology images M Veta, PJ van Diest, JPW Pluim Medical Imaging 2013: Digital Pathology 8676, 867607, 2013 | 46 | 2013 |
| Cutting out the middleman: measuring nuclear area in histopathology slides without segmentation M Veta, PJ Van Diest, JPW Pluim International conference on medical image computing and computer-assisted …, 2016 | 29 | 2016 |
| A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging Z Xiong, Q Xia, Z Hu, N Huang, C Bian, Y Zheng, S Vesal, N Ravikumar, ... Medical Image Analysis 67, 101832, 2021 | 23 | 2021 |
| Deep‐learning‐based preprocessing for quantitative myocardial perfusion MRI CM Scannell, M Veta, ADM Villa, EC Sammut, J Lee, M Breeuwer, ... Journal of Magnetic Resonance Imaging 51 (6), 1689-1696, 2020 | 22 | 2020 |
| Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge VM Campello, P Gkontra, C Izquierdo, C Martín-Isla, A Sojoudi, PM Full, ... IEEE Transactions on Medical Imaging, 2021 | 20 | 2021 |
| Deep learning regression for prostate cancer detection and grading in bi-parametric MRI C De Vente, P Vos, M Hosseinzadeh, J Pluim, M Veta IEEE Transactions on Biomedical Engineering 68 (2), 374-383, 2020 | 16 | 2020 |
| Progressively trained convolutional neural networks for deformable image registration KAJ Eppenhof, MW Lafarge, M Veta, JPW Pluim IEEE transactions on medical imaging 39 (5), 1594-1604, 2019 | 16 | 2019 |
