David Robben
David Robben
KU Leuven, ESAT/PSI
Verified email at kuleuven.be
Title
Cited by
Cited by
Year
ISLES 2015-A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI
O Maier, BH Menze, J von der Gablentz, L Häni, MP Heinrich, M Liebrand, ...
Medical image analysis 35, 250-269, 2017
2752017
ISLES 2016 and 2017-benchmarking ischemic stroke lesion outcome prediction based on multispectral MRI
S Winzeck, A Hakim, R McKinley, JA Pinto, V Alves, C Silva, M Pisov, ...
Frontiers in neurology 9, 679, 2018
742018
Simultaneous segmentation and anatomical labeling of the cerebral vasculature
D Robben, E Türetken, S Sunaert, V Thijs, G Wilms, P Fua, F Maes, ...
Medical image analysis 32, 201-215, 2016
302016
Benefits of deep learning for delineation of organs at risk in head and neck cancer
J Van der Veen, S Willems, S Deschuymer, D Robben, W Crijns, F Maes, ...
Radiotherapy and Oncology 138, 68-74, 2019
252019
Prediction of final infarct volume from native CT perfusion and treatment parameters using deep learning
D Robben, AMM Boers, HA Marquering, LLCM Langezaal, YB Roos, ...
Medical image analysis 59, 101589, 2020
192020
A Voxel-wise, cascaded classification approach to ischemic stroke lesion segmentation
D Robben, D Christiaens, JR Rangarajan, J Gelderblom, P Joris, F Maes, ...
BrainLes 2015, 254-265, 2015
172015
A reliable and time‐saving semiautomatic spike‐template–based analysis of interictal EEG–f MRI
S Tousseyn, P Dupont, D Robben, K Goffin, S Sunaert, W Van Paesschen
Epilepsia 55 (12), 2048-2058, 2014
162014
Simultaneous segmentation and anatomical labeling of the cerebral vasculature
D Robben, E Türetken, S Sunaert, V Thijs, G Wilms, P Fua, F Maes, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2014
132014
Anatomical labeling of the Circle of Willis using maximum a posteriori graph matching
D Robben, S Sunaert, V Thijs, G Wilms, F Maes, P Suetens
International Conference on Medical Image Computing and Computer-Assisted …, 2013
82013
Optimization with soft dice can lead to a volumetric bias
J Bertels, D Robben, D Vandermeulen, P Suetens
International MICCAI Brainlesion Workshop, 89-97, 2019
72019
Perfusion parameter estimation using neural networks and data augmentation
D Robben, P Suetens
International MICCAI brainlesion workshop, 439-446, 2018
62018
Clinical implementation of DeepVoxNet for auto-delineation of organs at risk in head and neck cancer patients in radiotherapy
S Willems, W Crijns, ALG Saint-Esteven, J Van Der Veen, D Robben, ...
OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy …, 2018
62018
Whole liver segmentation based on deep learning and manual adjustment for clinical use in SIRT
X Tang, EJ Rangraz, W Coudyzer, J Bertels, D Robben, G Schramm, ...
European journal of nuclear medicine and molecular imaging 47 (12), 2742-2752, 2020
52020
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
52020
Detection of vertebral fractures in CT using 3D convolutional neural networks
J Nicolaes, S Raeymaeckers, D Robben, G Wilms, D Vandermeulen, ...
International Workshop and Challenge on Computational Methods and Clinical …, 2019
52019
The role of medical image computing and machine learning in healthcare
F Maes, D Robben, D Vandermeulen, P Suetens
Artificial Intelligence in Medical Imaging, 9-23, 2019
52019
DeepVoxNet: voxel‐wise prediction for 3D images
D Robben, J Bertels, S Willems, D Vandermeulen, F Maes, P Suetens
52018
Contra-lateral information CNN for core lesion segmentation based on native CTP in acute stroke
J Bertels, D Robben, D Vandermeulen, P Suetens
International MICCAI Brainlesion Workshop, 263-270, 2018
42018
Segmentation of head-and-neck organs-at-risk in longitudinal CT scans combining deformable registrations and convolutional neural networks
L Vandewinckele, S Willems, D Robben, J Van Der Veen, W Crijns, ...
Computer Methods in Biomechanics and Biomedical Engineering: Imaging …, 2020
32020
Automated DWI analysis can identify patients within the thrombolysis time window of 4.5 hours
A Wouters, B Cheng, S Christensen, P Dupont, D Robben, B Norrving, ...
Neurology 90 (18), e1570-e1577, 2018
32018
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