Thomas de Bel
Thomas de Bel
PhD Candidate, Radboud University Medical Center, Computational Pathology Group
Geverifieerd e-mailadres voor radboudumc.nl
Titel
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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
3322017
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
482020
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
372019
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
172018
Stain-Transforming Cycle-Consistent Generative Adversarial Networks for Improved Segmentation of Renal Histopathology.
T de Bel, M Hermsen, J Kers, J van der Laak, GJS Litjens
MIDL, 151-163, 2019
162019
Automated gleason grading of prostate biopsies using deep learning
W Bulten, H Pinckaers, H van Boven, R Vink, T de Bel, B van Ginneken, ...
arXiv preprint arXiv:1907.07980, 2019
102019
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
22019
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
12020
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
12018
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
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Artikelen 1–12