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
391 2019 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
341 2020 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
70 2020 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
65 2020 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
60 2020 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
37 2021 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
32 2020 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
27 2020 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
26 2021 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
22 2022 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
22 2019 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
18 2021 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
14 2019 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
13 2023 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
10 2020 Reversibility of Diffusion-Weighted Imaging Lesions in Patients With Ischemic Stroke in the WAKE-UP Trial L Scheldeman, A Wouters, J Bertels, P Dupont, B Cheng, M Ebinger, ...
Stroke 54 (6), 1560-1568, 2023
9 2023 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
9 2021 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
8 2023 The Dice Loss in the Context of Missing or Empty Labels: Introducing S Tilborghs, J Bertels, D Robben, D Vandermeulen, F Maes
International Conference on Medical Image Computing and Computer-Assisted …, 2022
8 2022 DeepVoxNet: voxel-wise prediction for 3D images D Robben, J Bertels, S Willems, D Vandermeulen, F Maes, P Suetens
Medical Image Computing (ESAT/PSI), KU Leuven, Belgium, 2018
8 2018 
Vandermeulen DirkProfessor of medical and forensic image analysis KU Leuven ESAT/PSIПотвърден имейл адрес: kuleuven.be
