Thomas de Bel
Thomas de Bel
PhD Candidate, Radboud University Medical Center, Computational Pathology Group
Verified email at radboudumc.nl
Title
Cited by
Cited by
Year
Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge
AAA Setio, A Traverso, T De Bel, MSN Berens, C van den Bogaard, ...
Medical image analysis 42, 1-13, 2017
4142017
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
119*2020
Deep learning–based histopathologic assessment of kidney tissue
M Hermsen, T de Bel, M Den Boer, EJ Steenbergen, J Kers, S Florquin, ...
Journal of the American Society of Nephrology 30 (10), 1968-1979, 2019
702019
Stain-transforming cycle-consistent generative adversarial networks for improved segmentation of renal histopathology
T de Bel, M Hermsen, J Kers, J van der Laak, G Litjens
International Conference on Medical Imaging with Deep Learning, 151-163, 2019
292019
Automatic segmentation of histopathological slides of renal tissue using deep learning
T de Bel, M Hermsen, B Smeets, L Hilbrands, J van der Laak, G Litjens
Medical Imaging 2018: Digital Pathology 10581, 1058112, 2018
222018
Impact of rescanning and normalization on convolutional neural network performance in multi-center, whole-slide classification of prostate cancer
Z Swiderska-Chadaj, T de Bel, L Blanchet, A Baidoshvili, D Vossen, ...
Scientific RepoRtS 10 (1), 1-14, 2020
52020
Renal phospholipidosis and impaired magnesium handling in high‐fat‐diet–fed mice
S Kurstjens, B Smeets, C Overmars-Bos, HB Dijkman, DJW den Braanker, ...
The FASEB Journal 33 (6), 7192-7201, 2019
42019
Residual cyclegan for robust domain transformation of histopathological tissue slides
T de Bel, JM Bokhorst, J van der Laak, G Litjens
Medical Image Analysis 70, 102004, 2021
22021
Structure Instance Segmentation in Renal Tissue: A Case Study on Tubular Immune Cell Detection
T de Bel, M Hermsen, G Litjens, J van der Laak
Computational Pathology and Ophthalmic Medical Image Analysis, 112-119, 2018
22018
Optimized tumour infiltrating lymphocyte assessment for triple negative breast cancer prognostics
MCA Balkenhol, F Ciompi, Ż Świderska-Chadaj, R van de Loo, M Intezar, ...
The Breast 56, 78-87, 2021
2021
Discrimination of benign breast disease from normal lobules using an automated computational pathology algorithm
AC Degnim, T de Bel, ME Sherman, DC Radisky, SJ Winham, TL Hoskin, ...
Cancer Research 80 (16 Supplement), 2113-2113, 2020
2020
Development of an Automated Computational Pathology Algorithm Using Maching Learning to Quantify Levels of Breast Lobular Involution
AC Degnim, T de Bel, ME Sherman, DC Radisky, SJ Winham, TL Hoskin, ...
ANNALS OF SURGICAL ONCOLOGY 27 (SUPPL 1), S107-S108, 2020
2020
DEEP-LEARNING BASED HISTOPATHOLOGICAL ASSESSMENT OF RENAL TISSUE AS AN AID FOR KIDNEY TRANSPLANT RESEARCH
M Hermsen, T de Bel, M den Boer, E Steenbergen, J Kers, S Florquin, ...
TRANSPLANT INTERNATIONAL 32, 133-133, 2019
2019
The system can't perform the operation now. Try again later.
Articles 1–13