Tal Arbel
Tal Arbel
Professor of Electrical & Computer Engineering, McGill University
Verified email at - Homepage
Cited by
Cited by
The multimodal brain tumor image segmentation benchmark (BRATS)
BH Menze, A Jakab, S Bauer, J Kalpathy-Cramer, K Farahani, J Kirby, ...
IEEE transactions on medical imaging 34 (10), 1993-2024, 2014
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ...
arXiv preprint arXiv:1811.02629, 2018
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support: Third International Workshop, DLMIA 2017, and 7th International Workshop, ML-CDS …
MJ Cardoso, T Arbel, G Carneiro, T Syeda-Mahmood, JMRS Tavares, ...
Springer, 2017
Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge
K Murphy, B Van Ginneken, JM Reinhardt, S Kabus, K Ding, X Deng, ...
IEEE transactions on medical imaging 30 (11), 1901-1920, 2011
Computational Pathology and Ophthalmic Medical Image Analysis: First International Workshop, COMPAY 2018, and 5th International Workshop, OMIA 2018, Held in Conjunction with …
MJ Cardoso, T Arbel
Springer, 2018
Exploring uncertainty measures in deep networks for multiple sclerosis lesion detection and segmentation
T Nair, D Precup, DL Arnold, T Arbel
Medical image analysis 59, 101557, 2020
Longitudinal multiple sclerosis lesion segmentation: resource and challenge
A Carass, S Roy, A Jog, JL Cuzzocreo, E Magrath, A Gherman, J Button, ...
NeuroImage 148, 77-102, 2017
Why rankings of biomedical image analysis competitions should be interpreted with care
L Maier-Hein, M Eisenmann, A Reinke, S Onogur, M Stankovic, P Scholz, ...
Nature communications 9 (1), 5217, 2018
Medical sam adapter: Adapting segment anything model for medical image segmentation
J Wu, R Fu, H Fang, Y Liu, Z Wang, Y Xu, Y Jin, T Arbel
arXiv preprint arXiv:2304.12620, 2023
Evaluating intensity normalization on MRIs of human brain with multiple sclerosis
M Shah, Y Xiao, N Subbanna, S Francis, DL Arnold, DL Collins, T Arbel
Medical image analysis 15 (2), 267-282, 2011
Common limitations of image processing metrics: A picture story
A Reinke, MD Tizabi, CH Sudre, M Eisenmann, T Rädsch, M Baumgartner, ...
arXiv preprint arXiv:2104.05642, 2021
Metrics reloaded: Pitfalls and recommendations for image analysis validation
L Maier-Hein, B Menze
arXiv. org, 2022
Evaluating white matter lesion segmentations with refined Sørensen-Dice analysis
A Carass, S Roy, A Gherman, JC Reinhold, A Jesson, T Arbel, O Maier, ...
Scientific reports 10 (1), 8242, 2020
Detection, localization, and sex classification of faces from arbitrary viewpoints and under occlusion
M Toews, T Arbel
IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (9), 1567-1581, 2008
Feature-based morphometry: Discovering group-related anatomical patterns
M Toews, W Wells III, DL Collins, T Arbel
NeuroImage 49 (3), 2318-2327, 2010
Accounting for variance in machine learning benchmarks
X Bouthillier, P Delaunay, M Bronzi, A Trofimov, B Nichyporuk, J Szeto, ...
Proceedings of Machine Learning and Systems 3, 747-769, 2021
Viewpoint selection by navigation through entropy maps
T Arbel, FP Ferrie
Proceedings of the Seventh IEEE International Conference on Computer Vision …, 1999
Identifying the best machine learning algorithms for brain tumor segmentation
S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ...
progression assessment, and overall survival prediction in the BRATS …, 2018
Evaluation of state-of-the-art segmentation algorithms for left ventricle infarct from late Gadolinium enhancement MR images
R Karim, P Bhagirath, P Claus, RJ Housden, Z Chen, Z Karimaghaloo, ...
Medical image analysis 30, 95-107, 2016
IBIS: an OR ready open-source platform for image-guided neurosurgery
S Drouin, A Kochanowska, M Kersten-Oertel, IJ Gerard, R Zelmann, ...
International journal of computer assisted radiology and surgery 12, 363-378, 2017
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