| A survey on deep learning in medical image analysis G Litjens, T Kooi, BE Bejnordi, AAA Setio, F Ciompi, M Ghafoorian, ... Medical image analysis 42, 60-88, 2017 | 9821 | 2017 |
| 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 | 2334 | 2017 |
| From detection of individual metastases to classification of lymph node status at the patient level: the camelyon17 challenge P Bandi, O Geessink, Q Manson, M Van Dijk, M Balkenhol, M Hermsen, ... IEEE transactions on medical imaging 38 (2), 550-560, 2018 | 358 | 2018 |
| 1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset G Litjens, P Bandi, B Ehteshami Bejnordi, O Geessink, M Balkenhol, ... GigaScience 7 (6), giy065, 2018 | 265 | 2018 |
| Stain specific standardization of whole-slide histopathological images BE Bejnordi, G Litjens, N Timofeeva, I Otte-Höller, A Homeyer, ... IEEE transactions on medical imaging 35 (2), 404-415, 2015 | 250 | 2015 |
| 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 | 223 | 2019 |
| The importance of stain normalization in colorectal tissue classification with convolutional networks F Ciompi, O Geessink, BE Bejnordi, GS De Souza, A Baidoshvili, G Litjens, ... 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017 …, 2017 | 188 | 2017 |
| Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images BE Bejnordi, G Zuidhof, M Balkenhol, M Hermsen, P Bult, B van Ginneken, ... Journal of Medical Imaging 4 (4), 044504-044504, 2017 | 176 | 2017 |
| Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies B Ehteshami Bejnordi, M Mullooly, RM Pfeiffer, S Fan, PM Vacek, ... Modern Pathology 31 (10), 1502-1512, 2018 | 171 | 2018 |
| Conditional channel gated networks for task-aware continual learning D Abati, J Tomczak, T Blankevoort, S Calderara, R Cucchiara, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 134 | 2020 |
| Stain normalization of histopathology images using generative adversarial networks FG Zanjani, S Zinger, BE Bejnordi, JAWM van der Laak, PHN de With 2018 IEEE 15th International symposium on biomedical imaging (ISBI 2018 …, 2018 | 117 | 2018 |
| Automated detection of DCIS in whole-slide H&E stained breast histopathology images BE Bejnordi, M Balkenhol, G Litjens, R Holland, P Bult, N Karssemeijer, ... IEEE transactions on medical imaging 35 (9), 2141-2150, 2016 | 99 | 2016 |
| Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology images BE Bejnordi, J Lin, B Glass, M Mullooly, GL Gierach, ME Sherman, ... 2017 IEEE 14th international symposium on biomedical imaging (ISBI 2017 …, 2017 | 78 | 2017 |
| Computer aided quantification of intratumoral stroma yields an independent prognosticator in rectal cancer OGF Geessink, A Baidoshvili, JM Klaase, B Ehteshami Bejnordi, ... Cellular oncology 42, 331-341, 2019 | 75 | 2019 |
| Batch-Shaping for Learning Conditional Channel Gated Networks B Ehteshami Bejnordi, T Blankevoort, M Welling Proceedings of the eights International Conference on Learning …, 2020 | 59* | 2020 |
| A multi-scale superpixel classification approach to the detection of regions of interest in whole slide histopathology images BE Bejnordi, G Litjens, M Hermsen, N Karssemeijer, JAWM van der Laak Medical Imaging 2015: Digital Pathology 9420, 99-104, 2015 | 53 | 2015 |
| Quantitative analysis of stain variability in histology slides and an algorithm for standardization BE Bejnordi, N Timofeeva, I Otte-Höller, N Karssemeijer, ... Medical Imaging 2014: Digital Pathology 9041, 45-51, 2014 | 43 | 2014 |
| Histopathology stain-color normalization using deep generative models FG Zanjani, S Zinger, BE Bejnordi, JAWM van der Laak Medical Imaging with Deep Learning, 2018 | 39 | 2018 |
| Frameexit: Conditional early exiting for efficient video recognition A Ghodrati, BE Bejnordi, A Habibian Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 38 | 2021 |
| Automated segmentation of free-lying cell nuclei in pap smears for malignancy-associated change analysis R Moshavegh, BE Bejnordi, A Mehnert, K Sujathan, P Malm, E Bengtsson 2012 Annual International Conference of the IEEE Engineering in Medicine and …, 2012 | 35 | 2012 |
Jeroen van der LaakRadboud University Medical CenterVerified email at radboudumc.nl
