Maschenka Balkenhol
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
4772017
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
472016
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
462017
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
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
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
H and E stain augmentation improves generalization of convolutional networks for histopathological mitosis detection
D Tellez, M Balkenhol, N Karssemeijer, G Litjens, J van der Laak, ...
Medical Imaging 2018: Digital Pathology 10581, 105810Z, 2018
72018
Sonographic phenotypes of molecular subtypes of invasive ductal cancer in automated 3-D breast ultrasound
JCM van Zelst, M Balkenhol, T Tan, M Rutten, M Imhof-Tas, P Bult, ...
Ultrasound in medicine & biology 43 (9), 1820-1828, 2017
62017
Convolutional Neural Networks for Lymphocyte detection in Immunohistochemically Stained Whole-Slide Images
Z Swiderska-Chadaj, H Pinckaers, M van Rijthoven, M Balkenhol, ...
42018
Deep learning and manual assessment show that the absolute mitotic count does not contain prognostic information in triple negative breast cancer
MCA Balkenhol, P Bult, D Tellez, W Vreuls, PC Clahsen, F Ciompi, ...
Cellular Oncology, 1-15, 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
A generic nuclei detection method for histopathological breast images
H Kost, A Homeyer, P Bult, MCA Balkenhol, JAWM van der Laak, ...
Medical Imaging 2016: Digital Pathology 9791, 97911E, 2016
22016
Deep learning enables fully automated mitotic density assessment in breast cancer histopathology
M Balkenhol, P Bult, D Tellez, W Vreuls, P Clahsen, F Ciompi, ...
VIRCHOWS ARCHIV 475, S58-S59, 2019
2019
Deep learning assisted mitotic counting for breast cancer
MCA Balkenhol, D Tellez, W Vreuls, PC Clahsen, H Pinckaers, F Ciompi, ...
Laboratory Investigation, 1, 2019
2019
From Point Annotations to Epithelial Cell Detection in Breast Cancer Histopathology using RetinaNet
C Mercan, M Balkenhol, J van der Laak, F Ciompi
2019
Prognostic value of clinicopathological features in a large cohort of triple negative breast cancer
M Balkenhol, W Vreuls, C Wauters, S Mol, J van der Laak, P Bult
VIRCHOWS ARCHIV 473, S199-S199, 2018
2018
Deep Learning Based Algorithms Significantly Aid Breast Cancer Histopathology
J van der Laak, BE Bejnordi, DT Martin, P Bandi, MCA Balkenhol, P Bult, ...
JOURNAL OF PATHOLOGY 243, S4-S4, 2017
2017
Digital pattern recognition can aid H&E based breast histopathological diagnosis
M Balkenhol, BE Bejnordi, R Holland, M Hermsen, N Timofeeva, ...
EUROPEAN JOURNAL OF CANCER 57, S145-S146, 2016
2016
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