Portrait of Tal Arbel

Tal Arbel

Core Academic Member
Canada CIFAR AI Chair
Full Professor, McGill University, Department of Electrical and Computer Engineering

Biography

Tal Arbel is a professor in the Department of Electrical and Computer Engineering at McGill University, where she is the director of the Probabilistic Vision Group and Medical Imaging Lab in the Centre for Intelligent Machines.

She is also a Canada CIFAR AI Chair, an associate academic member of Mila – Quebec Artificial Intelligence Institute and an associate member of the Goodman Cancer Research Centre.

Arbel’s research focuses on the development of probabilistic deep learning methods in computer vision and medical image analysis for a wide range of real-world applications, with a focus on neurological diseases.

She is a recipient of the 2019 McGill Engineering Christophe Pierre Research Award and regularly serves on organizing committees for major international conferences in computer vision and medical image analysis, including for the Medical Image Computing and Computer-Assisted Intervention Society/MICCAI, the Medical Imaging with Deep Learning/MIDL, the International Conference on Computer Vision/ICCV or the Computer Vision and Pattern Recognition Conference/CVPR). She co-founded the arXiv overlay journal, Machine Learning for Biomedical Imaging (MELBA) and is currently its editor-in-chief.

Current Students

Master's Research - McGill University
Master's Research - McGill University
PhD - McGill University
Master's Research - McGill University
Master's Research - McGill University
Master's Research - McGill University
Master's Research - McGill University
Master's Research - McGill University

Publications

Challenging Conventional Segmentation Evaluation Metrics Focal Pathology ( Lesion and Tumour ) Segmentation from Patient Images
How can we do better ? Pitfalls in biomedical challenge design and how to address them
Annika Reinke
Matthias Eisenmann
Sinan Onogur
Marko Stankovic
Patrick Scholz
Hrvoje Bogunovic
Andrew P. Bradley
Aaron
Carass
Carolin Feldmann
Alejandro F. Frangi
Peter M. Full
Bram Ginneken Van
Ginneken
Allan Hanbury
Katrin Honauer
Michal Kozubek
Adam Bennett
Landman … (see 22 more)
Keno März
Oskar Maier
Klaus Maier-Hein
Bjoern Menze
Henning Müller
Peter F. Neher
Wiro Niessen
Nasir Rajpoot
Catherine Gregory
Sharp
Korsuk Sirinukunwattana
Stefanie Speidel
Christian Stock
Danail
Stoyanov
Abdel Aziz Taha
F. V. D. Sommen
Ching-Wei Wang
Marc-André Weber
Guoyan Zheng
Pierre Jannin
Lena Maier-Hein
Since the first MICCAI grand challenge was organized in 2007 [1], the impact of biomedical image analysis challenges on both the research fi… (see more)eld as well as on individual careers has been steadily growing. For example, the acceptance of a journal article today often depends on the performance of a new algorithm being assessed against the state-ofthe-art work on publicly available challenge datasets. Furthermore, the results are also important for the individuals scientific careers as well as the potential that algorithms can be translated into clinical practice. Yet, while the publication of papers in scientific journals and prestigious conferences, such as MICCAI, undergoes strict quality control, the design and organization of challenges do not. To investigate the effect of common practice, we have formed an international initiative dedicated to analyzing and improving a variety of aspects related to biomedical challenge design, execution and reporting [2]. In the first part of our abstract presentation at LABELS workshop, we are going to present some of the major pitfalls related to biomedical image analysis challenges today. Specifically, we will look at the following research questions: RQ1: How robust are challenge rankings? What is the effect of – the specific test cases used? – the specific metric variant(s) applied? – the rank aggregation method chosen (e.g. aggregation of metric values with the mean vs median)? ? Shared first/senior authors.
Predicting Future Disease Activity and Treatment Responders for Multiple Sclerosis Patients Using a Bag-of-Lesions Brain Representation
Andrew Doyle
Douglas Arnold
Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics
M. Cardoso
Enzo Ferrante
Xavier Pennec
Adrian Dalca
Sarah Parisot
S. Joshi
Nematollah Batmanghelich
Aristeidis Sotiras
Mads Lenstrup Nielsen
M. Sabuncu
Tom Fletcher
Li Shen
Stanley Durrleman
Stefan H. Sommer
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support
M. Cardoso
G. Carneiro
T. Syeda-Mahmood
J. Tavares
Mehdi Moradi
Andrew P. Bradley
Hayit Greenspan
J. Papa
Anant. Madabhushi
Jacinto C Nascimento
Jaime S. Cardoso
Vasileios Belagiannis
Zhi Lu
Faculdade Engenharia
Computer Assisted and Robotic Endoscopy and Clinical Image-Based Procedures
M. Cardoso
Xiongbiao Luo
Stefan Wesarg
Tobias Reichl
M. Ballester
Jonathan Mcleod
Klaus Dr. Drechsler
T. Peters
Marius Erdt
Kensaku Mori
M. Linguraru
Andreas Uhl
Cristina Oyarzun Laura
R. Shekhar
Computer Assisted and Robotic Endoscopy and Clinical Image-Based Procedures
M. Cardoso
Xiongbiao Luo
Stefan Wesarg
Tobias Reichl
M. Ballester
Jonathan Mcleod
Klaus Dr. Drechsler
T. Peters
Marius Erdt
Kensaku Mori
M. Linguraru
Andreas Uhl
Cristina Oyarzun Laura
R. Shekhar
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support
M. Cardoso
G. Carneiro
T. Syeda-Mahmood
J. Tavares
Mehdi Moradi
Andrew P. Bradley
Hayit Greenspan
J. Papa
Anant. Madabhushi
Jacinto C Nascimento
Jaime S. Cardoso
Vasileios Belagiannis
Zhi Lu
Faculdade Engenharia
Fetal, Infant and Ophthalmic Medical Image Analysis
M. Cardoso
Andrew Melbourne
Hrvoje Bogunovic
Pim Moeskops
Xinjian Chen
Ernst Schwartz
M. Garvin
E. Robinson
E. Trucco
Michael Ebner
Yanwu Xu
Antonios Makropoulos
Adrien Desjardin
Tom Kamiel Magda Vercauteren
Fetal, Infant and Ophthalmic Medical Image Analysis
M. Cardoso
Andrew Melbourne
Hrvoje Bogunovic
Pim Moeskops
Xinjian Chen
Ernst Schwartz
M. Garvin
E. Robinson
E. Trucco
Michael Ebner
Yanwu Xu
Antonios Makropoulos
Adrien Desjardin
Tom Kamiel Magda Vercauteren
Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics
M. Cardoso
Enzo Ferrante
Xavier Pennec
Adrian Dalca
Sarah Parisot
S. Joshi
Nematollah Batmanghelich
Aristeidis Sotiras
Mads Lenstrup Nielsen
Mert R. Sabuncu
Tom Fletcher
Li Shen
Stanley Durrleman
Stefan H. Sommer
Intravascular Imaging and Computer Assisted Stenting and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis
M. Cardoso
Su-Lin Lee
Veronika Cheplygina
Simone Balocco
Diana Mateus
Guillaume Zahnd
Lena Maier-Hein
Stefanie Demirci
Éric Granger
Luc Duong
M. Carbonneau
Shadi N. Albarqouni
G. Carneiro