Следене
Jeroen Bertels
Jeroen Bertels
Потвърден имейл адрес: kuleuven.be
Заглавие
Позовавания
Позовавания
Година
Optimizing the dice score and jaccard index for medical image segmentation: Theory and practice
J Bertels, T Eelbode, M Berman, D Vandermeulen, F Maes, R Bisschops, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
3122019
Optimization for medical image segmentation: theory and practice when evaluating with dice score or jaccard index
T Eelbode, J Bertels, M Berman, D Vandermeulen, F Maes, R Bisschops, ...
IEEE transactions on medical imaging 39 (11), 3679-3690, 2020
2572020
Whole liver segmentation based on deep learning and manual adjustment for clinical use in SIRT
X Tang, E Jafargholi Rangraz, W Coudyzer, J Bertels, D Robben, ...
European journal of nuclear medicine and molecular imaging 47, 2742-2752, 2020
532020
Effect of lower third molar segmentations on automated tooth development staging using a convolutional neural network
R Merdietio Boedi, N Banar, J De Tobel, J Bertels, D Vandermeulen, ...
Journal of Forensic Sciences 65 (2), 481-486, 2020
512020
Towards fully automated third molar development staging in panoramic radiographs
N Banar, J Bertels, F Laurent, RM Boedi, J De Tobel, P Thevissen, ...
International Journal of Legal Medicine 134, 1831-1841, 2020
502020
Optimization with soft dice can lead to a volumetric bias
J Bertels, D Robben, D Vandermeulen, P Suetens
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2020
312020
Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients
S Tilborghs, I Dirks, L Fidon, S Willems, T Eelbode, J Bertels, B Ilsen, ...
arXiv preprint arXiv:2007.15546, 2020
272020
Post training uncertainty calibration of deep networks for medical image segmentation
AJ Rousseau, T Becker, J Bertels, MB Blaschko, D Valkenborg
2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 1052-1056, 2021
252021
Cross-modal distillation to improve MRI-based brain tumor segmentation with missing MRI sequences
M Rahimpour, J Bertels, A Radwan, H Vandermeulen, S Sunaert, ...
IEEE Transactions on Biomedical Engineering 69 (7), 2153-2164, 2021
242021
Theoretical analysis and experimental validation of volume bias of soft Dice optimized segmentation maps in the context of inherent uncertainty
J Bertels, D Robben, D Vandermeulen, P Suetens
Medical Image Analysis 67, 101833, 2021
192021
Contra-lateral information CNN for core lesion segmentation based on native CTP in acute stroke
J Bertels, D Robben, D Vandermeulen, P Suetens
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2019
192019
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019
J Bertels, T Eelbode, M Berman, D Vandermeulen, F Maes, R Bisschops, ...
Lect Notes Comput Sc 10, 978-3, 2019
122019
Deep learning-based dental implant recognition using synthetic X-ray images
A Kohlakala, J Coetzer, J Bertels, D Vandermeulen
Medical & Biological Engineering & Computing 60 (10), 2951-2968, 2022
112022
On the relationship between calibrated predictors and unbiased volume estimation
T Popordanoska, J Bertels, D Vandermeulen, F Maes, MB Blaschko
Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021
102021
Explainable-by-design semi-supervised representation learning for covid-19 diagnosis from ct imaging
AD Berenguer, H Sahli, B Joukovsky, M Kvasnytsia, I Dirks, ...
arXiv preprint arXiv:2011.11719, 2020
102020
DeepVoxNet: voxel‐wise prediction for 3D images
D Robben, J Bertels, S Willems, D Vandermeulen, F Maes, P Suetens
92018
Dice semimetric losses: Optimizing the dice score with soft labels
Z Wang, T Popordanoska, J Bertels, R Lemmens, MB Blaschko
International Conference on Medical Image Computing and Computer-Assisted …, 2023
52023
Improving T1w MRI-based brain tumor segmentation using cross-modal distillation
M Rahimpour, J Bertels, D Vandermeulen, F Maes, K Goffin, M Koole
Medical Imaging 2021: Image Processing 11596, 261-268, 2021
52021
USE-evaluator: Performance metrics for medical image segmentation models supervised by uncertain, small or empty reference annotations in neuroimaging
S Ostmeier, B Axelrod, F Isensee, J Bertels, M Mlynash, S Christensen, ...
Medical Image Analysis 90, 102927, 2023
42023
Convolutional neural networks for medical image segmentation
J Bertels, D Robben, R Lemmens, D Vandermeulen
arXiv preprint arXiv:2211.09562, 2022
42022
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