Eugene Vorontsov
Eugene Vorontsov
Verified email at polymtl.ca
Title
Cited by
Cited by
Year
The importance of skip connections in biomedical image segmentation
M Drozdzal, E Vorontsov, G Chartrand, S Kadoury, C Pal
Deep Learning and Data Labeling for Medical Applications, 179-187, 2016
4222016
Deep Learning: A Primer for Radiologists
G Chartrand, PM Cheng, E Vorontsov, M Drozdzal, S Turcotte, CJ Pal, ...
RadioGraphics 37 (7), 2113-2131, 2017
2862017
Learning normalized inputs for iterative estimation in medical image segmentation
M Drozdzal, G Chartrand, E Vorontsov, M Shakeri, L Di Jorio, A Tang, ...
Medical Image Analysis, 2017
1352017
On orthogonality and learning recurrent networks with long term dependencies
E Vorontsov, C Trabelsi, S Kadoury, C Pal
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
1142017
The liver tumor segmentation benchmark (lits)
P Bilic, PF Christ, E Vorontsov, G Chlebus, H Chen, Q Dou, CW Fu, X Han, ...
arXiv preprint arXiv:1901.04056, 2019
1022019
A large annotated medical image dataset for the development and evaluation of segmentation algorithms
AL Simpson, M Antonelli, S Bakas, M Bilello, K Farahani, B van Ginneken, ...
arXiv preprint arXiv:1902.09063, 2019
992019
Liver lesion segmentation informed by joint liver segmentation
E Vorontsov, A Tang, C Pal, S Kadoury
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018
482018
Dynamics and Distribution of Klothoβ (KLB) and Fibroblast Growth Factor Receptor-1 (FGFR1) in Living Cells Reveal the Fibroblast Growth Factor-21 (FGF21)-induced Receptor Complex
AYK Ming, E Yoo, EN Vorontsov, SM Altamentova, DM Kilkenny, ...
Journal of Biological Chemistry 287 (24), 19997-20006, 2012
352012
Deep Learning for Automated Segmentation of Liver Lesions at CT in Patients with Colorectal Cancer Liver Metastases
E Vorontsov, M Cerny, P Régnier, L Di Jorio, CJ Pal, R Lapointe, ...
Radiology: Artificial Intelligence 1 (2), 180014, 2019
232019
Metastatic liver tumor segmentation using texture-based omni-directional deformable surface models
E Vorontsov, N Abi-Jaoudeh, S Kadoury
International MICCAI Workshop on Computational and Clinical Challenges in …, 2014
192014
Metastatic liver tumour segmentation with a neural network-guided 3D deformable model
E Vorontsov, A Tang, D Roy, CJ Pal, S Kadoury
Medical & biological engineering & computing, 1-13, 2016
172016
Towards non-saturating recurrent units for modelling long-term dependencies
S Chandar, C Sankar, E Vorontsov, SE Kahou, Y Bengio
Proceedings of the AAAI Conference on Artificial Intelligence 33, 3280-3287, 2019
152019
Metastatic liver tumour segmentation from discriminant Grassmannian manifolds
S Kadoury, E Vorontsov, A Tang
Physics in Medicine & Biology 60 (16), 6459, 2015
152015
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics
G Kerg, K Goyette, MP Touzel, G Gidel, E Vorontsov, Y Bengio, G Lajoie
Advances in Neural Information Processing Systems, 13613-13623, 2019
142019
Towards semi-supervised segmentation via image-to-image translation
E Vorontsov, P Molchanov, C Beckham, W Byeon, S De Mello, V Jampani, ...
arXiv preprint arXiv:1904.01636, 2019
6*2019
On Medical Image Segmentation and on Modeling Long Term Dependencies
E Vorontsov
Polytechnique Montréal, 2020
2020
Revealing Fibroblast Growth Factor Receptor-1 and Klotho-Beta Plasma Membrane Dynamics with FRAP and Number and Brightness Analysis
AY Ming, E Yoo, E Vorontsov, S Altamenova, JV Rocheleau
Biophysical Journal 102 (3), 666a, 2012
2012
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Articles 1–17