| 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 | 5083 | 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 | 1081 | 2017 |
| Pulmonary nodule detection in ct images: false positive reduction using multi-view convolutional networks AAA Setio, F Ciompi, G Litjens, P Gerke, C Jacobs, SJ van Riel, ... IEEE transactions on medical imaging 35 (5), 1160-1169, 2016 | 719 | 2016 |
| Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis G Litjens, CI Sánchez, N Timofeeva, M Hermsen, I Nagtegaal, I Kovacs, ... Scientific reports 6 (1), 1-11, 2016 | 594 | 2016 |
| Large scale deep learning for computer aided detection of mammographic lesions T Kooi, G Litjens, B van Ginneken, A Gubern-Mérida, CI Sánchez, R Mann, ... Medical Image Analysis 35, 303-312, 2017 | 523 | 2017 |
| Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge G Litjens, R Toth, W van de Ven, C Hoeks, S Kerkstra, B van Ginneken, ... Medical Image Analysis, 2013 | 326 | 2013 |
| Computer-aided detection of prostate cancer in MRI G Litjens, O Debats, J Barentsz, N Karssemeijer, H Huisman IEEE transactions on medical imaging 33 (5), 1083-1092, 2014 | 269 | 2014 |
| 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 | 159 | 2015 |
| Location sensitive deep convolutional neural networks for segmentation of white matter hyperintensities M Ghafoorian, N Karssemeijer, T Heskes, IWM Uden, CI Sanchez, ... Scientific Reports 7 (1), 5110, 2017 | 158 | 2017 |
| Assessment of prostate cancer aggressiveness using dynamic contrast-enhanced magnetic resonance imaging at 3 T EK Vos, GJS Litjens, T Kobus, T Hambrock, CA Hulsbergen-van de Kaa, ... European urology 64 (3), 448-455, 2013 | 157 | 2013 |
| A large annotated medical image dataset for the development and evaluation of segmentation algorithms AL Simpson, M Antonelli, S Bakas, M Bilello, K Farahani, B van Ginneken, ... arXiv preprint arXiv:1902.09063, 2019 | 147 | 2019 |
| Using deep learning to segment breast and fibroglandular tissue in MRI volumes MU Dalmış, G Litjens, K Holland, A Setio, R Mann, N Karssemeijer, ... Medical physics 44 (2), 533-546, 2017 | 126 | 2017 |
| Differentiation of prostatitis and prostate cancer by using diffusion-weighted MR imaging and MR-guided biopsy at 3 T KNA Nagel, MG Schouten, T Hambrock, GJS Litjens, CMA Hoeks, ... Radiology 267 (1), 164-172, 2013 | 117 | 2013 |
| 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 | 104 | 2017 |
| Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study W Bulten, H Pinckaers, H van Boven, R Vink, T de Bel, B van Ginneken, ... The Lancet Oncology 21 (2), 233-241, 2020 | 99* | 2020 |
| 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 | 94 | 2018 |
| 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 | 90 | 2017 |
| In-depth tissue profiling using multiplexed immunohistochemical consecutive staining on single slide R Remark, T Merghoub, N Grabe, G Litjens, D Damotte, JD Wolchok, ... Science Immunology 1 (1), aaf6925-aaf6925, 2016 | 79 | 2016 |
| 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 | 78 | 2018 |
| Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks D Tellez, M Balkenhol, I Otte-Höller, R van de Loo, R Vogels, P Bult, ... IEEE transactions on medical imaging 37 (9), 2126-2136, 2018 | 77 | 2018 |
Jeroen van der LaakRadboud University Medical CenterVerified email at radboudumc.nl
