| 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 | 3461 | 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 | 732 | 2017 |
| 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 | 126 | 2015 |
| 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 | 71 | 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, 2017 | 70 | 2017 |
| 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 | 53 | 2019 |
| 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 | 53 | 2016 |
| Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies BE Bejnordi, M Mullooly, RM Pfeiffer, S Fan, PM Vacek, DL Weaver, ... Modern Pathology 31 (10), 1502-1512, 2018 | 48 | 2018 |
| 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 | 46 | 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 | 46 | 2018 |
| 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 | 37 | 2017 |
| 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 | 27 | 2012 |
| 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 | 24 | 2018 |
| 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, 94200H, 2015 | 21 | 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, 904108, 2014 | 19 | 2014 |
| Novel chromatin texture features for the classification of pap smears BE Bejnordi, R Moshavegh, K Sujathan, P Malm, E Bengtsson, A Mehnert Medical Imaging 2013: Digital Pathology 8676, 867608, 2013 | 12 | 2013 |
| Histopathology stain-color normalization using deep generative models FG Zanjani, S Zinger, BE Bejnordi, JAWM van der Laak | 11 | 2018 |
| 3D volume reconstruction from serial breast specimen radiographs for mapping between histology and 3D whole specimen imaging T Mertzanidou, JH Hipwell, S Reis, DJ Hawkes, B Ehteshami Bejnordi, ... Medical physics 44 (3), 935-948, 2017 | 11 | 2017 |
| Batch-Shaping for Learning Conditional Channel Gated Networks B Ehteshami Bejnordi, T Blankevoort, M Welling arXiv, arXiv: 1907.06627, 2019 | 8* | 2019 |
| Automated detection of prostate cancer in digitized whole-slide images of H and E-stained biopsy specimens G Litjens, BE Bejnordi, N Timofeeva, G Swadi, I Kovacs, ... Medical Imaging 2015: Digital Pathology 9420, 94200B, 2015 | 8 | 2015 |
Jeroen van der LaakRadboud University Medical CenterVerified email at radboudumc.nl
