Hans Pinckaers
Hans Pinckaers
PhD candidate, Radboud University Medical Center, Computational Pathology Group
Verified email at - Homepage
Cited by
Cited by
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
Learning to detect lymphocytes in immunohistochemistry with deep learning
Z Swiderska-Chadaj, H Pinckaers, M van Rijthoven, M Balkenhol, ...
Medical image analysis 58, 101547, 2019
Deep learning assisted mitotic counting for breast cancer
MCA Balkenhol, D Tellez, W Vreuls, PC Clahsen, H Pinckaers, F Ciompi, ...
Laboratory investigation 99 (11), 1596-1606, 2019
Urinating standing versus sitting: position is of influence in men with prostate enlargement. A systematic review and meta-analysis
Y de Jong, JHFM Pinckaers, RM ten Brinck, AAB Lycklama ā Nijeholt, ...
PloS one 9 (7), e101320, 2014
Streaming convolutional neural networks for end-to-end learning with multi-megapixel images
H Pinckaers, B van Ginneken, G Litjens
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019
Learning from sparsely annotated data for semantic segmentation in histopathology images
JM Bokhorst, H Pinckaers, P van Zwam, I Nagtegaal, J van der Laak, ...
International Conference on Medical Imaging with Deep Learning--Full Paper Track, 2018
Mobile e‐diary application facilitates the monitoring of patient‐reported outcomes and a high treatment adherence for clinical trials in dermatology
M Rijsbergen, T Niemeyer‐van der Kolk, R Rijneveld, J Pinckaers, ...
Journal of the European Academy of Dermatology and Venereology 34 (3), 633-639, 2020
Neural ordinary differential equations for semantic segmentation of individual colon glands
H Pinckaers, G Litjens
arXiv preprint arXiv:1910.10470, 2019
Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge
W Bulten, K Kartasalo, PHC Chen, P Ström, H Pinckaers, K Nagpal, Y Cai, ...
Nature medicine, 1-10, 2022
Detection of prostate cancer in whole-slide images through end-to-end training with image-level labels
H Pinckaers, W Bulten, J Van der Laak, G Litjens
IEEE Transactions on Medical Imaging 40 (7), 1817 - 1826, 2021
Convolutional neural networks for lymphocyte detection in immunohistochemically stained whole-slide images
Z Swiderska-Chadaj, H Pinckaers, M van Rijthoven, M Balkenhol, ...
The PANDA challenge: Prostate cANcer graDe Assessment using the Gleason grading system
W Bulten, S Pinckaers, K Eklund
MICCAI challenge, 2020
Training convolutional neural networks with megapixel images
H Pinckaers, G Litjens
arXiv preprint arXiv:1804.05712, 2018
Influence of voiding posture on urodynamic parameters in men: a literature review
Y De Jong, J Pinckaers, RM Ten Brinck, AAB Lycklama ā Nijeholt
TvU 4, 36-42, 2014
Artificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer in Biopsies—Current Status and Next Steps
K Kartasalo, W Bulten, B Delahunt, PHC Chen, H Pinckaers, H Olsson, ...
European Urology Focus 7 (4), 687-691, 2021
End-to-end classification on basal-cell carcinoma histopathology whole-slides images
DJ Geijs, H Pinckaers, AL Amir, GJS Litjens
Medical Imaging 2021: Digital Pathology 11603, 1160307, 2021
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, 0
Multi-class semantic cell segmentation and classification of aplasia in bone marrow histology images
L van Eekelen, H Pinckaers, KM Hebeda, G Litjens
Medical Imaging 2020: Digital Pathology 11320, 113200B, 2020
High resolution whole prostate biopsy classification using streaming stochastic gradient descent
H Pinckaers, W Bulten, G Litjens
Medical Imaging 2019: Digital Pathology 10956, 35-40, 2019
Gleason grading of prostate cancer using artificial intelligence: lessons learned from the PANDA challenge
K Kartasalo, P Ström, M Eklund, W Bulten, H Pinckaers, G Litjens, ...
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