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Gijs van Tulder
Gijs van Tulder
Verified email at cs.ru.nl - Homepage
Title
Cited by
Cited by
Year
Theano: A Python framework for fast computation of mathematical expressions
R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ...
arXiv e-prints, arXiv: 1605.02688, 2016
1177*2016
Combining generative and discriminative representation learning for lung CT analysis with convolutional restricted Boltzmann machines
G van Tulder, M de Bruijne
IEEE Transactions on Medical Imaging 35 (5), 1262-1272, 2016
1732016
Multi-task attention-based semi-supervised learning for medical image segmentation
S Chen, G Bortsova, A García-Uceda Juárez, G Tulder, M Bruijne
International Conference on Medical Image Computing and Computer-Assisted …, 2019
1472019
Why does synthesized data improve multi-sequence classification?
G van Tulder, M de Bruijne
International Conference on Medical Image Computing and Computer-Assisted …, 2015
1112015
Learning Cross-Modality Representations from Multi-Modal Images
G van Tulder, M de Bruijne
IEEE Transactions on Medical Imaging, 2018
532018
Question classification by weighted combination of lexical, syntactic and semantic features
B Loni, G van Tulder, P Wiggers, DMJ Tax, M Loog
Text, Speech and Dialogue, 243-250, 2011
482011
Multi-view analysis of unregistered medical images using cross-view transformers
G van Tulder, Y Tong, E Marchiori
International Conference on Medical Image Computing and Computer-Assisted …, 2021
442021
Weakly supervised object detection with 2D and 3D regression neural networks
F Dubost, H Adams, P Yilmaz, G Bortsova, G van Tulder, MA Ikram, ...
Medical Image Analysis 65, 101767, 2020
402020
Learning features for tissue classification with the classification restricted Boltzmann machine
G van Tulder, M de Bruijne
International MICCAI workshop on medical computer vision, 47-58, 2014
322014
An end-to-end approach to segmentation in medical images with CNN and posterior-CRF
S Chen, ZS Gamechi, F Dubost, G van Tulder, M de Bruijne
Medical Image Analysis 76, 102311, 2022
242022
Storing hierarchical data in a database
G van Tulder
SitePoint Pty. Ltd. http://www.sitepoint.com/article/hierarchical-data-database, 2003
19*2003
Segmentation of intracranial arterial calcification with deeply supervised residual dropout networks
G Bortsova, G van Tulder, F Dubost, T Peng, N Navab, A van der Lugt, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2017
182017
Representation learning for cross-modality classification
G van Tulder, M de Bruijne
MICCAI Workshop on Medical Computer Vision, 2016
132016
Diaphragmatic dysfunction in neuromuscular disease, an MRI study
L Harlaar, P Ciet, G van Tulder, E Brusse, RGM Timmermans, ...
Neuromuscular Disorders 32 (1), 15-24, 2022
102022
Automated Segmentation and Volume Measurement of Intracranial Internal Carotid Artery Calcification at Noncontrast CT
G Bortsova, D Bos, F Dubost, MW Vernooij, MK Ikram, G van Tulder, ...
Radiology: Artificial Intelligence, e200226, 2021
102021
Chest MRI to diagnose early diaphragmatic weakness in Pompe disease
L Harlaar, P Ciet, G van Tulder, A Pittaro, HA van Kooten, ...
Orphanet journal of rare diseases 16 (1), 1-12, 2021
92021
Label Refinement Network from Synthetic Error Augmentation for Medical Image Segmentation
S Chen, AG Uceda, J Su, G van Tulder, L Wolff, T van Walsum, ...
arXiv preprint arXiv:2209.06353, 2022
22022
Elastic deformations for N-dimensional images (Python SciPy NumPy TensorFlow)
G van Tulder
http://doi.org/10.5281/zenodo.4569691, 2018
22018
PHP Frontend to ImageMagick
G van Tulder
evolt.org, 2003
22003
Unpaired, unsupervised domain adaptation assumes your domains are already similar
G van Tulder, M de Bruijne
Medical Image Analysis, 102825, 2023
12023
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