Florian Dubost
Florian Dubost
Postdoctoral Researcher, Stanford University
Verified email at stanford.edu
Title
Cited by
Cited by
Year
GP-Unet: Lesion detection from weak labels with a 3D regression network
F Dubost, G Bortsova, H Adams, A Ikram, WJ Niessen, M Vernooij, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2017
412017
Gray matter age prediction as a biomarker for risk of dementia
J Wang, MJ Knol, A Tiulpin, F Dubost, M de Bruijne, MW Vernooij, ...
Proceedings of the National Academy of Sciences 116 (42), 21213-21218, 2019
30*2019
Enlarged perivascular spaces in brain MRI: Automated quantification in four regions
F Dubost, P Yilmaz, H Adams, G Bortsova, MA Ikram, W Niessen, ...
NeuroImage 185, 534-544, 2019
252019
3D regression neural network for the quantification of enlarged perivascular spaces in brain MRI
F Dubost, H Adams, G Bortsova, MA Ikram, W Niessen, M Vernooij, ...
Medical image analysis 51, 89-100, 2019
202019
Semi-supervised medical image segmentation via learning consistency under transformations
G Bortsova, F Dubost, L Hogeweg, I Katramados, M de Bruijne
International Conference on Medical Image Computing and Computer-Assisted …, 2019
142019
Deep learning from label proportions for emphysema quantification
G Bortsova, F Dubost, S Ørting, I Katramados, L Hogeweg, L Thomsen, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2018
142018
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
82017
Hands-free segmentation of medical volumes via binary inputs
F Dubost, L Peter, C Rupprecht, BG Becker, N Navab
Deep Learning and Data Labeling for Medical Applications, 259-268, 2016
72016
Automated lesion detection by regressing intensity-based distance with a neural network
KMH van Wijnen, F Dubost, P Yilmaz, MA Ikram, WJ Niessen, H Adams, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2019
62019
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
52020
Multi-atlas image registration of clinical data with automated quality assessment using ventricle segmentation
F Dubost, M de Bruijne, M Nardin, AV Dalca, KL Donahue, AK Giese, ...
Medical Image Analysis, 101698, 2020
5*2020
Hydranet: data augmentation for regression neural networks
F Dubost, G Bortsova, H Adams, MA Ikram, W Niessen, M Vernooij, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2019
32019
Patient-Specific Conditional Joint Models of Shape, Image Features and Clinical Indicators
B Egger, MD Schirmer, F Dubost, MJ Nardin, NS Rost, P Golland
International Conference on Medical Image Computing and Computer-Assisted …, 2019
22019
Event-Based Modeling with High-Dimensional Imaging Biomarkers for Estimating Spatial Progression of Dementia
V Venkatraghavan, F Dubost, EE Bron, WJ Niessen, M de Bruijne, S Klein, ...
International Conference on Information Processing in Medical Imaging, 169-180, 2019
22019
Quantification of lung abnormalities in cystic fibrosis using deep networks
F Marques, F Dubost, M Kemner-van de Corput, HAW Tiddens, ...
Medical Imaging 2018: Image Processing 10574, 105741G, 2018
22018
Spectral Data Augmentation Techniques to Quantify Lung Pathology from CT-Images
S Kayal, F Dubost, HAWM Tiddens, M de Bruijne
2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 586-590, 2020
12020
APIR-Net: Autocalibrated Parallel Imaging Reconstruction Using a Neural Network
C Zhang, F Dubost, M de Bruijne, S Klein, DHJ Poot
International Workshop on Machine Learning for Medical Image Reconstruction …, 2019
12019
Segmentation of White Matter Hyperintensities with an Ensemble of Multi-Dimensional Convolutional Gated Recurrent Units
R Camarasa, C Doue, M de Bruijne, F Dubost
https://wmh.isi.uu.nl/wp-content/uploads/2018/08/coroflo.pdf, 2018
12018
Let's Hope it Works! Inaccurate Supervision of Neural Networks with Incorrect Labels: Application to Epilepsy
F Dubost, E Hong, DY Fu, N Bhaskhar, S Tang, K Saab, D Rubin, ...
arXiv preprint arXiv:2011.14101, 2020
2020
DS6: Deformation-aware learning for small vessel segmentation with small, imperfectly labeled dataset
S Chatterjee, K Prabhu, M Pattadkal, G Bortsova, F Dubost, H Mattern, ...
arXiv preprint arXiv:2006.10802, 2020
2020
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Articles 1–20