Oscar Geessink
Oscar Geessink
PhD candidate, Dept. of Pathology, Radboud University Medical Center
Verified email at radboudumc.nl - Homepage
TitleCited byYear
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
4752017
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
562017
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
282018
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
242018
Camelyon17: Grand challenge on cancer metastasis detection and classification in lymph nodes
O Geessink, P Bándi, G Litjens, J van der Laak
82017
Convolutional Neural Networks for Lymphocyte detection in Immunohistochemically Stained Whole-Slide Images
Z Swiderska-Chadaj, H Pinckaers, M van Rijthoven, M Balkenhol, ...
42018
Computer aided quantification of intratumoral stroma yields an independent prognosticator in rectal cancer
OGF Geessink, A Baidoshvili, JM Klaase, BE Bejnordi, GJS Litjens, ...
Cellular Oncology 42 (3), 331-341, 2019
32019
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
22019
Toward automatic segmentation and quantification of tumor and stroma in whole-slide images of H and E stained rectal carcinomas
OGF Geessink, A Baidoshvili, G Freling, JM Klaase, CH Slump, ...
Medical Imaging 2015: Digital Pathology 9420, 94200F, 2015
22015
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