Portrait de Julien Cohen-Adad

Julien Cohen-Adad

Membre académique associé
Professeur agrégé, Polytechnique Montréal, Département de génie électrique
Professeur asssocié, Université de Montréal, Département de neurosciences
Sujets de recherche
Apprentissage automatique médical
Site web
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Biographie

Julien Cohen-Adad est professeur à Polytechnique Montréal et directeur associé de l'Unité de neuro-imagerie fonctionnelle de l'Université de Montréal. Il est également titulaire de la Chaire de recherche du Canada en imagerie par résonance magnétique quantitative. Ses recherches portent sur l'avancement des méthodes de neuro-imagerie avec l'aide de l'IA. Voici quelques exemples de ses projets :

- Formation multimodale pour les tâches d'imagerie médicale (segmentation des pathologies, diagnostic, etc.);

- Ajout d'un a priori issu de la physique de l'IRM pour améliorer la généralisation des modèles;

- Incorporation de mesures d'incertitude pour traiter la variabilité interévaluateurs;

- Stratégies d'apprentissage continu lorsque le partage des données est restreint;

- Introduction des méthodes d'IA dans la routine de la radiologie clinique par l’intermédiaire de solutions logicielles conviviales.

Le professeur Cohen-Adad dirige également de nombreux projets de logiciels libres qui profitent à la communauté scientifique et clinique. Plus de détails sur https://neuro.polymtl.ca/software.html.

En résumé, Julien aime : l'IRM avec des aimants puissants, la neuro-imagerie, la programmation et la science ouverte!

Étudiants actuels

Kahina Baouche
Stagiaire de recherche - Polytechnique
Github
Pierre Louis Benveniste
Doctorat - Polytechnique
Co-superviseur⋅e :
Hervé Lombaert
Site web
Github
Google Scholar
Armand Collin
Doctorat - Polytechnique
Github
Thomas Dagonneau
Maîtrise recherche - Polytechnique
Naga Karthik Enamundram
Doctorat - Polytechnique
Co-superviseur⋅e :
Sarath Chandar
Site web
Github
Google Scholar
Paul Hoareau
Maîtrise recherche - Polytechnique
Github
Youssef Laatar
Maîtrise recherche - Polytechnique
Github
Julien Laborde-Peyré
Stagiaire de recherche - Polytechnique
Github
Nilser Laines Medina
Doctorat - Polytechnique
Nathan Molinier
Doctorat - Polytechnique
Github
Kalum Ost
Collaborateur·rice de recherche
Arthur Toulouse
Maîtrise recherche - Polytechnique
Github

Publications

Erratum to: Rapid simultaneous acquisition of macromolecular tissue volume, susceptibility, and relaxometry maps (Magn Reson Med. 2022;87:781‐790.)
Fang Frank Yu
Susie Yi Huang
Ashwin Kumar
Thomas Witzel
Congyu Liao
Tanguy Duval
Julien Cohen-Adad
Berkin Bilgic
2022-02-09
Magnetic Resonance in Medicine (publié)
doi.org
Brain-spinal cord interaction in long-term motor sequence learning in human: An fMRI study
Ali Khatibi
Shahabeddin Vahdat
Ovidiu Lungu
Jürgen Finsterbusch
Christian Büchel
Julien Cohen-Adad
Veronique Marchand-Pauvert
Julien Doyon
2021-12-31
NeuroImage (publié)
doi.org
Titre: Title: Comparison of Myelin Imaging Techniques in Ex Vivo Spinal Cord Auteur:
Nikola Stikov
Julien Cohen-Adad
Manh-Tung Vuong
Vuong Manh Tung
Myelin is a dielectric material that wraps around the axons of nerve fibers to enable fast conduction of signals throughout the nervous syst… (voir plus)em. Loss of myelin can cause anywhere from minor interruption to complete disruption of nerve impulses in a range of neurodegenerative diseases such as multiple sclerosis and Parkinson’s disease. There is an ongoing debate in the myelin imaging community about which biomarker based on Magnetic Resonance Imaging (MRI) is more correlated with myelin. In this work, we implemented and compared several MRI-based myelin imaging techniques (quantitative magnetization transfer imaging, myelin water imaging, and proton density imaging) by evaluating their repeatability and their relation to large-scale histology in the ex vivo spinal cords of a rat, a dog, and a human. While there are studies investigating the relationship between pairs of them as well as with histology, to the best of our knowledge, this is the first study that implemented and compared all those methods at the same time to evaluate their reproducibility and their correlation with myelin. Qualitatively the contrasts were similar, and all techniques had comparable scan-rescan and correlations with histology. Surprisingly, the voxel-wise correlations between the various myelin measures were almost as high as the scan-rescan correlations. The correlations decreased when only white matter was considered, which could be due to the small dynamic range of the measurement, or due to artifacts related to the preparation and panoramic scanning of the tissue. We conclude that the myelin imaging techniques explored in this thesis exhibit similar specificity to myelin, yet the histological correlations suggest that more work is needed to determine the optimal myelin imaging protocol. The study also pointed out some potential miscalibrations during acquisitions as well as data processing that may lead to anywhere from minor to major impact on the accuracy of the results. These include B1 mapping, insufficient spoiling and variation of the predelay time. We have also standardized the data processing routines by upgrading qMTLab to qMRLab which adds several quantitative MR methods to the toolbox, such as standard T1 mapping and field mapping. In addition, the data of the dog spinal cord in this study will be published together with the analysis scripts to help the interested reader to reproduce the findings from this thesis.
2021-12-31
(publié)
www.semanticscholar.org
The Myelin-Weighted Connectome in Parkinson's Disease
Tommy Boshkovski
Julien Cohen-Adad
Bratislav Misic
Isabelle Arnulf
Jean-Christophe Corvol
Marie Vidailhet
Stéphane Lehéricy
Nikola Stikov
Matteo Mancini
Even though Parkinson's disease (PD) is typically viewed as largely affecting gray matter, there is growing evidence that there are also str… (voir plus)uctural changes in the white matter. Traditional connectomics methods that study PD may not be specific to underlying microstructural changes, such as myelin loss. The primary objective of this study is to investigate the PD‐induced changes in myelin content in the connections emerging from the basal ganglia and the brainstem. For the weighting of the connectome, we used the longitudinal relaxation rate as a biologically grounded myelin‐sensitive metric. We computed the myelin‐weighted connectome in 35 healthy control subjects and 81 patients with PD. We used partial least squares to highlight the differences between patients with PD and healthy control subjects. Then, a ring analysis was performed on selected brainstem and subcortical regions to evaluate each node's potential role as an epicenter for disease propagation. Then, we used behavioral partial least squares to relate the myelin alterations with clinical scores. Most connections (~80%) emerging from the basal ganglia showed a reduced myelin content. The connections emerging from potential epicentral nodes (substantia nigra, nucleus basalis of Meynert, amygdala, hippocampus, and midbrain) showed significant decrease in the longitudinal relaxation rate (P  0.05). This effect was not seen for the medulla and the pons. The myelin‐weighted connectome was able to identify alteration of the m
2021-12-21
Movement Disorders (inconnu)
doi.org
Minimum detectable spinal cord atrophy with automatic segmentation: Investigations using an open-access dataset of healthy participants
Paul Bautin
Julien Cohen-Adad
•Evaluate the robustness of an automated analysis pipeline for detecting SC atrophy.•Simulate spinal cord atrophy and scan-rescan variab… (voir plus)ility.•Fully automated analysis method available on an open access database.•Evaluation of sample size and inter/intra-subject variability for T1w and T2w images. Evaluate the robustness of an automated analysis pipeline for detecting SC atrophy. Simulate spinal cord atrophy and scan-rescan variability. Fully automated analysis method available on an open access database. Evaluation of sample size and inter/intra-subject variability for T1w and T2w images.
2021-10-03
NeuroImage : Clinical (publié)
doi.org
Author Correction: Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers
Julien Cohen-Adad
Eva Alonso‐Ortiz
Mihael Abramovic
Carina Arneitz
Nicole Atcheson
Laura Barlow
Robert L. Barry
Markus Barth
Marco Battiston
Christian Büchel
Matthew D. Budde
Virginie Callot
Anna J. E. Combes
Benjamin De Leener
Maxime Descoteaux
Paulo Loureiro de Sousa
Marek Dostál
Julien Doyon
Adam Dvorak
Falk Eippert … (voir 71 de plus)
Karla R. Epperson
Kevin S. Epperson
Patrick Freund
Jürgen Finsterbusch
Alexandru Foias
Michela Fratini
Issei Fukunaga
Claudia A. M. Gandini Wheeler-Kingshott
Giancarlo Germani
Guillaume Gilbert
Federico Giove
Charley Gros
Francesco Grussu
Akifumi Hagiwara
Pierre-Gilles Henry
Tomáš Horák
Masaaki Hori
James Joers
Kouhei Kamiya
Haleh Karbasforoushan
Miloš Keřkovský
Ali Khatibi
Joo‐Won Kim
Nawal Kinany
Hagen H. Kitzler
Shannon Kolind
Yazhuo Kong
Petr Kudlička
Paul Kuntke
Nyoman D. Kurniawan
Slawomir Kusmia
René Labounek
Maria Marcella Laganà
Cornelia Laule
Christine S. Law
Christophe Lenglet
Tobias Leutritz
Yaou Liu
Sara Llufriu
Sean Mackey
Eloy Martinez-Heras
Loan Mattera
Igor Nestrasil
Kristin P. O’Grady
Nico Papinutto
Daniel Papp
Deborah Pareto
Todd B. Parrish
Anna Pichiecchio
Ferran Prados
Àlex Rovira
Marc J. Ruitenberg
Rebecca S. Samson
Giovanni Savini
Maryam Seif
Alan C. Seifert
Alex K. Smith
Seth A. Smith
Zachary A. Smith
Elisabeth Solana
Y. Suzuki
George Tackley
Alexandra Tinnermann
Jan Valosek
Dimitri Van De Ville
Marios C. Yiannakas
Kenneth A. Weber
Nikolaus Weiskopf
Richard G. Wise
Patrik O. Wyss
Junqian Xu
2021-09-22
Scientific Data (publié)
doi.org
Stacked Hourglass Network with a Multi-level Attention Mechanism: Where to Look for Intervertebral Disc Labeling
Reza Azad
Lucas Rouhier
Julien Cohen-Adad
Labeling vertebral discs from MRI scans is important for the proper diagnosis of spinal related diseases, including multiple sclerosis, amyo… (voir plus)trophic lateral sclerosis, degenerative cervical myelopathy and cancer. Automatic labeling of the vertebral discs in MRI data is a difficult task because of the similarity between discs and bone area, the variability in the geometry of the spine and surrounding tissues across individuals, and the variability across scans (manufacturers, pulse sequence, image contrast, resolution and artefacts). In previous studies, vertebral disc labeling is often done after a disc detection step and mostly fails when the localization algorithm misses discs or has false positive detection. In this work, we aim to mitigate this problem by reformulating the semantic vertebral disc labeling using the pose estimation technique. To do so, we propose a stacked hourglass network with multi-level attention mechanism to jointly learn intervertebral disc position and their skeleton structure. The proposed deep learning model takes into account the strength of semantic segmentation and pose estimation technique to handle the missing area and false positive detection. To further improve the performance of the proposed method, we propose a skeleton-based search space to reduce false positive detection. The proposed method evaluated on spine generic public multi-center dataset and demonstrated better performance comparing to previous work, on both T1w and T2w contrasts. The method is implemented in ivadomed (https://ivadomed.org).
2021-09-20
Machine Learning in Medical Imaging (publié)
doi.org
arxiv.org
Team NeuroPoly: Description of the Pipelines for the MICCAI 2021 MS New Lesions Segmentation Challenge
Uzay Macar
Enamundram Naga Karthik
Charley Gros
Andréanne Lemay
Julien Cohen-Adad
This paper gives a detailed description of the pipelines used for the 2nd edition of the MICCAI 2021 Challenge on Multiple Sclerosis Lesion … (voir plus)Segmentation. An overview of the data preprocessing steps applied is provided along with a brief description of the pipelines used, in terms of the architecture and the hyperparameters. Our code for this work can be found at: https://github.com/ivadomed/ms-challenge-2021.
2021-09-11
ArXiv (prépublication)
arxiv.org
arxiv.org
Rapid simultaneous acquisition of macromolecular tissue volume, susceptibility, and relaxometry maps
Fang Frank Yu
Susie Yi Huang
Thomas Witzel
Ashwin Kumar
Congyu Liao
Tanguy Duval
Julien Cohen-Adad
Berkin Bilgic
Purpose A major obstacle to the clinical implementation of quantitative MR is the lengthy acquisition time required to derive multi-contrast… (voir plus) parametric maps. We sought to reduce the acquisition time for quantitative susceptibility mapping (QSM) and macromolecular tissue volume (MTV) by acquiring both contrasts simultaneously by leveraging their redundancies. The Joint Virtual Coil concept with generalized autocalibrating partially parallel acquisitions (JVC-GRAPPA) was applied to reduce acquisition time further. Methods Three adult volunteers were imaged on a 3T scanner using a multi-echo 3D GRE sequence acquired at three head orientations. MTV, QSM, R2*, T1, and proton density maps were reconstructed. The same sequence (GRAPPA R=4) was performed in subject #1 with a single head orientation for comparison. Fully sampled data was acquired in subject #2, from which retrospective undersampling was performed (R=6 GRAPPA and R=9 JVC-GRAPPA). Prospective undersampling was performed in subject #3 (R=6 GRAPPA and R=9 JVC-GRAPPA) using gradient blips to shift k-space sampling in later echoes. Results Subject #1’s multi-orientation and single-orientation MTV maps were not significantly different based on RMSE. For subject #2, the retrospectively undersampled JVC-GRAPPA and GRAPPA generated similar results as fully sampled data. This approach was validated with the prospectively undersampled images in subject #3. Using QSM, R2*, and MTV, the contributions of myelin and iron content to susceptibility was estimated. Conclusion We have developed a novel strategy to simultaneously acquire data for the reconstruction of five intrinsically co-registered 1-mm isotropic resolution multi-parametric maps, with a scan time of 6 minutes using JVC-GRAPPA.
2021-09-03
Magnetic Resonance in Medicine (publié)
doi.org
Quantitative 7-Tesla Imaging of Cortical Myelin Changes in Early Multiple Sclerosis
Valeria Barletta
Elena Herranz
Constantina A. Treaba
Ambica Mehndiratta
Russell Ouellette
Gabriel Mangeat
Tobias Granberg
Jacob A. Sloane
Eric C Klawiter
Julien Cohen-Adad
Caterina Mainero
Cortical demyelination occurs early in multiple sclerosis (MS) and relates to disease outcome. The brain cortex has endogenous propensity fo… (voir plus)r remyelination as proven from histopathology study. In this study, we aimed at characterizing cortical microstructural abnormalities related to myelin content by applying a novel quantitative MRI technique in early MS. A combined myelin estimation (CME) cortical map was obtained from quantitative 7-Tesla (7T) T2* and T1 acquisitions in 25 patients with early MS and 19 healthy volunteers. Cortical lesions in MS patients were classified based on their myelin content by comparison with CME values in healthy controls as demyelinated, partially demyelinated, or non-demyelinated. At follow-up, we registered changes in cortical lesions as increased, decreased, or stable CME. Vertex-wise analysis compared cortical CME in the normal-appearing cortex in 25 MS patients vs. 19 healthy controls at baseline and investigated longitudinal changes at 1 year in 10 MS patients. Measurements from the neurite orientation dispersion and density imaging (NODDI) diffusion model were obtained to account for cortical neurite/dendrite loss at baseline and follow-up. Finally, CME maps were correlated with clinical metrics. CME was overall low in cortical lesions (p = 0.03) and several normal-appearing cortical areas (p 0.05) in the absence of NODDI abnormalities. Individual cortical lesion analysis revealed, however, heterogeneous CME patterns from extensive to partial or absent demyelination. At follow-up, CME overall decreased in cortical lesions and non-lesioned cortex, with few areas showing an increase (p 0.05). Cortical CME maps correlated with processing speed in several areas across the cortex. In conclusion, CME allows detection of cortical microstructural changes related to coexisting demyelination and remyelination since the early phases of MS, and shows to be more sensitive than NODDI and relates to cognitive performance.
2021-09-02
Frontiers in Neurology (publié)
doi.org
Generic acquisition protocol for quantitative MRI of the spinal cord
Julien Cohen-Adad
Eva Alonso-Ortiz
Mihael Abramovic
Carina Arneitz
Nicole Atcheson
Laura Barlow
Robert L. Barry
Markus Barth
Marco Battiston
Christian Büchel
Matthew Budde
Virginie Callot
Anna J. E. Combes
Benjamin De Leener
Maxime Descoteaux
Paulo Loureiro de Sousa
Marek Dostál
Julien Cohen-Adad
Adam Dvorak
Falk Eippert … (voir 71 de plus)
Karla R. Epperson
Kevin S. Epperson
Patrick Freund
Jürgen Finsterbusch
Alexandru Foias
Michela Fratini
Issei Fukunaga
Claudia A. M. Gandini Wheeler-Kingshott
Giancarlo Germani
Guillaume Gilbert
Federico Giove
Charley Gros
Francesco Grussu
Akifumi Hagiwara
Pierre-Gilles Henry
Tomáš Horák
Masaaki Hori
James Joers
Kouhei Kamiya
Haleh Karbasforoushan
Miloš Keřkovský
Ali Khatibi
Joo-Won Kim
Nawal Kinany
Hagen Kitzler
Shannon Kolind
Yazhuo Kong
Petr Kudlička
Paul Kuntke
Nyoman D. Kurniawan
Slawomir Kusmia
René Labounek
Maria Marcella Laganà
Cornelia Laule
Christine S. Law
Christophe Lenglet
Tobias Leutritz
Yaou Liu
Sara Llufriu
Sean Mackey
Eloy Martinez-Heras
Loan Mattera
Igor Nestrasil
Kristin P. O’Grady
Nico Papinutto
Daniel Papp
Deborah Pareto
Todd B. Parrish
Anna Pichiecchio
Ferran Prados
Àlex Rovira
Marc J. Ruitenberg
Rebecca S. Samson
Giovanni Savini
Maryam Seif
Alan C. Seifert
Alex K. Smith
Seth A. Smith
Zachary A. Smith
Elisabeth Solana
Yuichi Suzuki
George Tackley
Alexandra Tinnermann
Jan Valosek
Dimitri Van De Ville
Marios C. Yiannakas
Kenneth A. Weber
Nikolaus Weiskopf
Richard G. Wise
Patrik O. Wyss
Junqian Xu
Optimized and standardized MRI acquisition protocols for the spinal cord, compatible with Siemens, GE and Philips scanners.
2021-08-15
Nature Protocols (publié)
doi.org
Open-access quantitative MRI data of the spinal cord and reproducibility across participants, sites and manufacturers
Julien Cohen-Adad
Eva Alonso-Ortiz
Mihael Abramovic
Carina Arneitz
Nicole Atcheson
Laura Barlow
Robert L. Barry
Markus Barth
Marco Battiston
Christian Büchel
Matthew Budde
Virginie Callot
Anna J. E. Combes
Benjamin De Leener
Maxime Descoteaux
Paulo Loureiro de Sousa
Marek Dostál
Julien Doyon
Adam Dvorak
Falk Eippert … (voir 71 de plus)
Karla R. Epperson
Kevin S. Epperson
Patrick Freund
Jürgen Finsterbusch
Alexandru Foias
Michela Fratini
Issei Fukunaga
Claudia A. M. Gandini Wheeler-Kingshott
Giancarlo Germani
Guillaume Gilbert
Federico Giove
Charley Gros
Francesco Grussu
Akifumi Hagiwara
Pierre-Gilles Henry
Tomáš Horák
Masaaki Hori
James Joers
Kouhei Kamiya
Haleh Karbasforoushan
Miloš Keřkovský
Ali Khatibi
Joo-Won Kim
Nawal Kinany
Hagen H. Kitzler
Shannon Kolind
Yazhuo Kong
Petr Kudlička
Paul Kuntke
Nyoman D. Kurniawan
Slawomir Kusmia
René Labounek
Maria Marcella Laganà
Cornelia Laule
Christine S. Law
Christophe Lenglet
Tobias Leutritz
Yaou Liu
Sara Llufriu
Sean Mackey
Eloy Martinez-Heras
Loan Mattera
Igor Nestrasil
Kristin P. O'Grady
Nico Papinutto
Daniel Papp
Deborah Pareto
Todd B. Parrish
Anna Pichiecchio
Ferran Prados
Àlex Rovira
Marc J. Ruitenberg
Rebecca S. Samson
Giovanni Savini
Maryam Seif
Alan C. Seifert
Alex K. Smith
Seth A. Smith
Zachary A. Smith
Elisabeth Solana
Y. Suzuki
George Tackley
Alexandra Tinnermann
Jan Valosek
Dimitri Van De Ville
Marios C. Yiannakas
Kenneth A. Weber II
Nikolaus Weiskopf
Richard G. Wise
Patrik O. Wyss
Junqian Xu
In a companion paper by Cohen-Adad et al. we introduce the spine generic quantitative MRI protocol that provides valuable metrics for assess… (voir plus)ing spinal cord macrostructural and microstructural integrity. This protocol was used to acquire a single subject dataset across 19 centers and a multi-subject dataset across 42 centers (for a total of 260 participants), spanning the three main MRI manufacturers: GE, Philips and Siemens. Both datasets are publicly available via git-annex. Data were analysed using the Spinal Cord Toolbox to produce normative values as well as inter/intra-site and inter/intra-manufacturer statistics. Reproducibility for the spine generic protocol was high across sites and manufacturers, with an average inter-site coefficient of variation of less than 5% for all the metrics. Full documentation and results can be found at https://spine-generic.rtfd.io/. The datasets and analysis pipeline will help pave the way towards accessible and reproducible quantitative MRI in the spinal cord.
2021-08-15
Scientific Data (publié)
doi.org