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David Robben
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2020 – today
- 2024
- [i19]Ezequiel de la Rosa, Mauricio Reyes, Sook-Lei Liew, Alexandre Hutton, Roland Wiest, Johannes Kaesmacher, Uta Hanning, Arsany Hakim, Richard Zubal, Waldo Valenzuela, David Robben, Diana Maria Sima, Vincenzo Anania, Arne Brys, James A. Meakin, Anne Mickan, Gabriel Broocks, Christian Heitkamp, Shengbo Gao, Kongming Liang, Ziji Zhang, Md Mahfuzur Rahman Siddiquee, Andriy Myronenko, Pooya Ashtari, Sabine Van Huffel, Hyun-su Jeong, Chiho Yoon, Chulhong Kim, Jiayu Huo, Sébastien Ourselin, Rachel Sparks, Albert Clèrigues, Arnau Oliver, Xavier Lladó, Liam F. Chalcroft, Ioannis Pappas, Jeroen Bertels, Ewout Heylen, Juliette Moreau, Nima Hatami, Carole Frindel, Abdul Qayyum, Moona Mazher, Domenec Puig, Shao-Chieh Lin, Chun-Jung Juan, Tianxi Hu, Lyndon Boone, Maged Goubran, Yi-Jui Liu, Susanne Wegener, Florian Kofler, Ivan Ezhov, Suprosanna Shit, Moritz Roman Hernandez Petzsche, Bjoern H. Menze, Jan S. Kirschke, Benedikt Wiestler:
A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge. CoRR abs/2403.19425 (2024) - [i18]Ezequiel de la Rosa, Ruisheng Su, Mauricio Reyes, Roland Wiest, Evamaria Olga Riedel, Florian Kofler, Kaiyuan Yang, Hakim Baazaoui, David Robben, Susanne Wegener, Jan S. Kirschke, Benedikt Wiestler, Bjoern H. Menze:
ISLES'24: Improving final infarct prediction in ischemic stroke using multimodal imaging and clinical data. CoRR abs/2408.10966 (2024) - [i17]Evamaria Olga Riedel, Ezequiel de la Rosa, The Anh Baran, Moritz Roman Hernandez Petzsche, Hakim Baazaoui, Kaiyuan Yang, David Robben, Joaquin Oscar Seia, Roland Wiest, Mauricio Reyes, Ruisheng Su, Claus Zimmer, Tobias Boeckh-Behrens, Maria Berndt, Bjoern H. Menze, Benedikt Wiestler, Susanne Wegener, Jan S. Kirschke:
ISLES 2024: The first longitudinal multimodal multi-center real-world dataset in (sub-)acute stroke. CoRR abs/2408.11142 (2024) - 2022
- [c16]Sofie Tilborghs, Jeroen Bertels, David Robben, Dirk Vandermeulen, Frederik Maes:
The Dice Loss in the Context of Missing or Empty Labels: Introducing $\varPhi $ and ε. MICCAI (5) 2022: 527-537 - [i16]Moritz Roman Hernandez Petzsche, Ezequiel de la Rosa, Uta Hanning, Roland Wiest, Waldo Enrique Valenzuela Pinilla, Mauricio Reyes, Maria Inês Meyer, Sook-Lei Liew, Florian Kofler, Ivan Ezhov, David Robben, Alexandre Hutton, Tassilo Friedrich, Teresa Zarth, Johannes Bürkle, The Anh Baran, Bjoern H. Menze, Gabriel Broocks, Lukas Meyer, Claus Zimmer, Tobias Boeckh-Behrens, Maria Berndt, Benno Ikenberg, Benedikt Wiestler, Jan S. Kirschke:
ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset. CoRR abs/2206.06694 (2022) - [i15]Sofie Tilborghs, Jeroen Bertels, David Robben, Dirk Vandermeulen, Frederik Maes:
The Dice loss in the context of missing or empty labels: Introducing Φ and ε. CoRR abs/2207.09521 (2022) - [i14]Jeroen Bertels, David Robben, Dirk Vandermeulen, Paul Suetens:
Theoretical analysis and experimental validation of volume bias of soft Dice optimized segmentation maps in the context of inherent uncertainty. CoRR abs/2211.04161 (2022) - [i13]Jeroen Bertels, David Robben, Dirk Vandermeulen, Robin Lemmens:
Final infarct prediction in acute ischemic stroke. CoRR abs/2211.04850 (2022) - [i12]Jeroen Bertels, David Robben, Robin Lemmens, Dirk Vandermeulen:
Convolutional neural networks for medical image segmentation. CoRR abs/2211.09562 (2022) - [i11]Jeroen Bertels, David Robben, Robin Lemmens, Dirk Vandermeulen:
DeepVoxNet2: Yet another CNN framework. CoRR abs/2211.09569 (2022) - 2021
- [j5]Jeroen Bertels, David Robben, Dirk Vandermeulen, Paul Suetens:
Theoretical analysis and experimental validation of volume bias of soft Dice optimized segmentation maps in the context of inherent uncertainty. Medical Image Anal. 67: 101833 (2021) - [j4]Ezequiel de la Rosa, Diana Maria Sima, Bjoern H. Menze, Jan S. Kirschke, David Robben:
AIFNet: Automatic vascular function estimation for perfusion analysis using deep learning. Medical Image Anal. 74: 102211 (2021) - [i10]Ezequiel de la Rosa, David Robben, Diana Maria Sima, Jan S. Kirschke, Bjoern H. Menze:
Differentiable Deconvolution for Improved Stroke Perfusion Analysis. CoRR abs/2103.17111 (2021) - 2020
- [j3]Liesbeth Vandewinckele, Siri Willems, David Robben, Julie Van Der Veen, Wouter Crijns, Sandra Nuyts, Frederik Maes:
Segmentation of head-and-neck organs-at-risk in longitudinal CT scans combining deformable registrations and convolutional neural networks. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 8(5): 519-528 (2020) - [j2]David Robben, Anna M. M. Boers, Henk A. Marquering, Lucianne L. C. M. Langezaal, Yvo B. W. E. M. Roos, Robert J. van Oostenbrugge, Wim H. van Zwam, Diederik W. J. Dippel, Charles B. L. M. Majoie, Aad van der Lugt, Robin Lemmens, Paul Suetens:
Prediction of final infarct volume from native CT perfusion and treatment parameters using deep learning. Medical Image Anal. 59 (2020) - [c15]Jaime Simarro Viana, Ezequiel de la Rosa, Thijs Vande Vyvere, David Robben, Diana Maria Sima:
Unsupervised 3D Brain Anomaly Detection. BrainLes@MICCAI (1) 2020: 133-142 - [c14]Ezequiel de la Rosa, David Robben, Diana Maria Sima, Jan S. Kirschke, Bjoern H. Menze:
Differentiable Deconvolution for Improved Stroke Perfusion Analysis. MICCAI (7) 2020: 593-602 - [i9]Mattias Billast, Maria Inês Meyer, Diana Maria Sima, David Robben:
Improved inter-scanner MS lesion segmentation by adversarial training on longitudinal data. CoRR abs/2002.00952 (2020) - [i8]Sofie Tilborghs, Ine Dirks, Lucas Fidon, Siri Willems, Tom Eelbode, Jeroen Bertels, Bart Ilsen, Arne Brys, Adriana Dubbeldam, Nico Buls, Panagiotis Gonidakis, Sebastián Amador Sánchez, Annemiek Snoeckx, Paul M. Parizel, Johan de Mey, Dirk Vandermeulen, Tom Vercauteren, David Robben, Dirk Smeets, Frederik Maes, Jef Vandemeulebroucke, Paul Suetens:
Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients. CoRR abs/2007.15546 (2020) - [i7]Ezequiel de la Rosa, Diana Maria Sima, Bjoern H. Menze, Jan S. Kirschke, David Robben:
AIFNet: Automatic Vascular Function Estimation for Perfusion Analysis Using Deep Learning. CoRR abs/2010.01617 (2020) - [i6]Jaime Simarro Viana, Ezequiel de la Rosa, Thijs Vande Vyvere, David Robben, Diana Maria Sima:
Unsupervised 3D Brain Anomaly Detection. CoRR abs/2010.04717 (2020) - [i5]Abel Díaz Berenguer, Hichem Sahli, Boris Joukovsky, Maryna Kvasnytsia, Ine Dirks, Mitchel Alioscha-Pérez, Nikos Deligiannis, Panagiotis Gonidakis, Sebastián Amador Sánchez, Redona Brahimetaj, Evgenia Papavasileiou, Jonathan Cheung-Wai Chan, Fei Li, Shangzhen Song, Yixin Yang, Sofie Tilborghs, Siri Willems, Tom Eelbode, Jeroen Bertels, Dirk Vandermeulen, Frederik Maes, Paul Suetens, Lucas Fidon, Tom Vercauteren, David Robben, Arne Brys, Dirk Smeets, Bart Ilsen, Nico Buls, Nina Watté, Johan de Mey, Annemiek Snoeckx, Paul M. Parizel, Julien Guiot, Louis Deprez, Paul Meunier, Stefaan Gryspeerdt, Kristof De Smet, Bart Jansen, Jef Vandemeulebroucke:
Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging. CoRR abs/2011.11719 (2020)
2010 – 2019
- 2019
- [c13]Jeroen Bertels, David Robben, Dirk Vandermeulen, Paul Suetens:
Optimization with Soft Dice Can Lead to a Volumetric Bias. BrainLes@MICCAI (1) 2019: 89-97 - [c12]Mattias Billast, Maria Inês Meyer, Diana Maria Sima, David Robben:
Improved Inter-scanner MS Lesion Segmentation by Adversarial Training on Longitudinal Data. BrainLes@MICCAI (1) 2019: 98-107 - [c11]Joeri Nicolaes, Steven Raeymaeckers, David Robben, Guido Wilms, Dirk Vandermeulen, Cesar Libanati, Marc Debois:
Detection of Vertebral Fractures in CT Using 3D Convolutional Neural Networks. CSI@MICCAI 2019: 3-14 - [i4]Joeri Nicolaes, Steven Raeymaeckers, David Robben, Guido Wilms, Dirk Vandermeulen, Cesar Libanati, Marc Debois:
Detection of vertebral fractures in CT using 3D Convolutional Neural Networks. CoRR abs/1911.01816 (2019) - [i3]Jeroen Bertels, David Robben, Dirk Vandermeulen, Paul Suetens:
Optimization with soft Dice can lead to a volumetric bias. CoRR abs/1911.02278 (2019) - 2018
- [c10]Liesbeth Vandewinckele, David Robben, Wouter Crijns, Frederik Maes:
Segmentation of Head and Neck Organs-At-Risk in Longitudinal CT Scans Combining Deformable Registrations and Convolutional Neural Networks. DLMIA/ML-CDS@MICCAI 2018: 146-154 - [c9]Siri Willems, Wouter Crijns, Agustina La Greca Saint-Esteven, Julie Van Der Veen, David Robben, Tom Depuydt, Sandra Nuyts, Karin Haustermans, Frederik Maes:
Clinical Implementation of DeepVoxNet for Auto-Delineation of Organs at Risk in Head and Neck Cancer Patients in Radiotherapy. OR 2.0/CARE/CLIP/ISIC@MICCAI 2018: 223-232 - [c8]Jeroen Bertels, David Robben, Dirk Vandermeulen, Paul Suetens:
Contra-Lateral Information CNN for Core Lesion Segmentation Based on Native CTP in Acute Stroke. BrainLes@MICCAI (1) 2018: 263-270 - [c7]David Robben, Paul Suetens:
Perfusion Parameter Estimation Using Neural Networks and Data Augmentation. BrainLes@MICCAI (1) 2018: 439-446 - [i2]David Robben, Paul Suetens:
Perfusion parameter estimation using neural networks and data augmentation. CoRR abs/1810.04898 (2018) - [i1]David Robben, Anna M. M. Boers, Henk A. Marquering, Lucianne L. C. M. Langezaal, Yvo B. W. E. M. Roos, Robert J. van Oostenbrugge, Wim H. van Zwam, Diederik W. J. Dippel, Charles B. L. M. Majoie, Aad van der Lugt, Robin Lemmens, Paul Suetens:
Prediction of final infarct volume from native CT perfusion and treatment parameters using deep learning. CoRR abs/1812.02496 (2018) - 2016
- [j1]David Robben, Engin Türetken, Stefan Sunaert, Vincent Thijs, Guy Willems, Pascal Fua, Frederik Maes, Paul Suetens:
Simultaneous segmentation and anatomical labeling of the cerebral vasculature. Medical Image Anal. 32: 201-215 (2016) - [c6]Niels Verheyen, David Robben, Daniel Ruijters, Vitor Mendes Pereira, Olivier Brina, Frederik Maes, Paul Suetens:
Inferring brain deformation during open neurosurgery using CBCT angiography. ISBI 2016: 111-114 - 2015
- [c5]David Robben, Daan Christiaens, Janaki Raman Rangarajan, Jaap Gelderblom, Philip Joris, Frederik Maes, Paul Suetens:
A Voxel-Wise, Cascaded Classification Approach to Ischemic Stroke Lesion Segmentation. Brainles@MICCAI 2015: 254-265 - [c4]David Robben, Stefan Sunaert, Vincent Thijs, Guy Willms, Frederik Maes, Paul Suetens:
Perfusion Paths: Inference of Voxelwise Blood Flow Trajectories in CT Perfusion. MICCAI (2) 2015: 407-414 - 2014
- [c3]David Robben, Engin Türetken, Stefan Sunaert, Vincent Thijs, Guy Willms, Pascal Fua, Frederik Maes, Paul Suetens:
Simultaneous Segmentation and Anatomical Labeling of the Cerebral Vasculature. MICCAI (1) 2014: 307-314 - 2013
- [c2]David Robben, Stefan Sunaert, Vincent Thijs, Guy Willms, Frederik Maes, Paul Suetens:
Anatomical Labeling of the Circle of Willis Using Maximum A Posteriori Graph Matching. MICCAI (1) 2013: 566-573 - 2012
- [c1]David Robben, Dirk Smeets, Daniel Ruijters, McElory Hoffmann, Laura Antanas, Frederik Maes, Paul Suetens:
Intra-patient Non-rigid Registration of 3D Vascular Cerebral Images. CLIP 2012: 106-113
Coauthor Index
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last updated on 2024-10-07 22:13 CEST by the dblp team
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