Portrait of Julien Cohen-Adad

Julien Cohen-Adad

Associate Academic Member
Associate Professor, Polytechnique Montréal, Electrical Engineering Department
Adjunct Professor, Université de Montréal, Department of Neuroscience
Research Topics
Medical Machine Learning
Website
Google Scholar
X

Biography

Julien Cohen-Adad is a professor at Polytechnique Montréal and the associate director of the Neuroimaging Functional Unit at Université de Montréal. He is also the Canada Research Chair in Quantitative Magnetic Resonance Imaging.

His research focuses on advancing neuroimaging methods with the help of AI. Some examples of projects are:

- Multi-modal training for medical imaging tasks (segmentation of pathologies, diagnosis, etc.)

- Adding prior from MRI physics to improve model generalization

- Incorporating uncertainty measures to deal with inter-rater variability

- Continuous learning strategies when data sharing is restricted

- Bringing AI methods into clinical radiology routine via user-friendly software solutions

Cohen-Adad also leads multiple open-source software projects that are benefiting the research and clinical community (see neuro.polymtl.ca/software.html). In short, he loves MRI with strong magnets, neuroimaging, programming and open science!

Current Students

Rohan Banerjee
Master's Research - Polytechnique Montréal
Co-supervisor :
Gauthier Gidel
Website
Github
Google Scholar
Pierre Louis Benveniste
PhD - Polytechnique Montréal
Co-supervisor :
Hervé Lombaert
Website
Github
Google Scholar
Armand Collin
PhD - Polytechnique Montréal
Github
Thomas Dagonneau
Master's Research - Polytechnique Montréal
Github
Naga Karthik Enamundram
PhD - Polytechnique Montréal
Co-supervisor :
Sarath Chandar
emvnagakarthik@gmail.com
Website
Github
Google Scholar
Nilser Laines Medina
PhD - Polytechnique Montréal
Nathan Molinier
PhD - Polytechnique Montréal
Github
Kalum Ost
Collaborating researcher
Abel Salmona Salmona
Research Intern - Polytechnique Montréal
abel.salmona@gmail.com
Github
Julien Thouveny
Master's Research - Université de Montréal
Arthur Toulouse
Master's Research - Polytechnique Montréal
Github
Jan Valosek
Postdoctorate - Polytechnique Montréal
Website
Github
Google Scholar

Publications

Impact of individual rater style on deep learning uncertainty in medical imaging segmentation
Olivier Vincent
Charley Gros
Julien Cohen-Adad
While multiple studies have explored the relation between inter-rater variability and deep learning model uncertainty in medical segmentatio… (see more)n tasks, little is known about the impact of individual rater style. This study quantifies rater style in the form of bias and consistency and explores their impacts when used to train deep learning models. Two multi-rater public datasets were used, consisting of brain multiple sclerosis lesion and spinal cord grey matter segmentation. On both datasets, results show a correlation (
2021-05-05
ArXiv (preprint)
arxiv.org
arxiv.org
Tracking white and grey matter degeneration along the spinal cord axis in degenerative cervical myelopathy
Kevin Vallotton
Gergely David
Markus Hupp
Nikolai Pfender
Julien Cohen-Adad
Michael Fehlings
Rebecca S. Samson
Claudia A. M. Gandini Wheeler-Kingshott
Armin Curt
Patrick Freund
Maryam Seif
Objective: To determine tissue-specific neurodegeneration across the spinal cord in patients with mild-moderate degenerative cervical myelop… (see more)athy (DCM). Methods: Twenty-four mild-moderate DCM and 24 healthy subjects were recruited. In patients, a T2-weighted scan was acquired at the compression site, while in all participants a T2*-weighted and diffusion-weighted scan was acquired at the cervical level (C2-C3) and in the lumbar enlargement (i.e. rostral and caudal to the site of compression). We quantified intramedullary signal changes, maximal canal and cord compression, white (WM) and grey matter (GM) atrophy, and microstructural indices from diffusion-weighted scans. All patients underwent clinical (modified Japanese Orthopaedic Association (mJOA)) and electrophysiological assessments. Regression analysis assessed associations between MRI readouts and electrophysiological and clinical outcomes. Results: Twenty patients were classified with mild and four with moderate DCM using the mJOA scale. The most frequent site of compression was at C5-C6 level with maximum cord compression of 4.68{+/-}0.83 mm. Ten patients showed imaging evidence of cervical myelopathy. In the cervical cord, WM and GM atrophy and WM microstructural changes were evident, while in the lumbar cord only WM showed atrophy and microstructural changes. Remote cervical cord WM microstructural changes were pronounced in patients with radiological myelopathy and associated with impaired electrophysiology. Lumbar cord WM atrophy was associated with lower limb sensory impairments. Conclusion: Tissue-specific neurodegeneration revealed by quantitative MRI, already apparent across the spinal cord in mild-moderate DCM prior to the onset of severe clinical impairments. WM microstructural changes are particularly sensitive to remote pathologically and clinically eloquent changes in DCM.
2021-04-22
medRxiv (preprint)
doi.org
Associations Between Relative Morning Blood Pressure, Cerebral Blood Flow, and Memory in Older Adults Treated and Controlled for Hypertension
Adrián Noriega de la Colina
Atef Badji
Marie-Christine Robitaille-Grou
Christine Gagnon
Tommy Boshkovski
Maxime Lamarre-cliche
Sven Joubert
Claudine J. Gauthier
Louis Bherer
Julien Cohen-Adad
Hélène Girouard
Supplemental Digital Content is available in the text. Hypertension, elevated morning blood pressure (BP) surges, and circadian BP variabili… (see more)ty constitute risk factors for cerebrovascular events. Nevertheless, while evidence indicates that hypertension is associated with cognitive dysfunctions, the link between BP variability and cognitive performance during aging is not clear. The purpose of this study is to determine the interaction between relative morning BP, cerebral blood flow (CBF) levels, and cognitive performance in hypertensive older adults with controlled BP under antihypertensive treatment. Eighty-four participants aged between 60 and 75 years old were separated into normotensive (n=51) and hypertensive (n=33) groups and underwent 24-hour ambulatory BP monitoring. They were also examined for CBF in the gray matter (CBF-GM) by magnetic resonance imaging and 5 cognitive domains: global cognition, working memory, episodic memory, processing speed, and executive functions. There was no difference in cognitive performance and CBF between normotensive and controlled hypertensive participants. Through a sensitivity analysis, we identified that, among relative morning BP variables, the best fit for CBF values in this cohort was the morning-evening difference in BP. The relative morning BP was negatively associated with CBF-GM in these hypertensive older adults only. In turn, CBF-GM levels were negatively associated with working and episodic memory scores in hypertensive older adults. This is the first extended study demonstrating an association between high relative morning BP and lower levels of CBF-GM, including the further impact of CBF-GM levels on the cognitive performance of specific domains in a community-based cohort of older adults with hypertension.
2021-03-29
HYPERTENSION (published)
doi.org