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
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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

Publications

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… (see more) 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.
2021-09-04
Magnetic Resonance in Medicine (published)
doi.org
Effectiveness of regional diffusion MRI measures in distinguishing multiple sclerosis abnormalities within the cervical spinal cord
Haykel Snoussi
Julien Cohen-Adad
Olivier Commowick
Benoit Combes
Elise Bannier
Slimane Tounekti
Anne Sophie Kerbrat
Christian Barillot
Emmanuel Caruyer
Multiple sclerosis (MS) is an inflammatory disorder of the central nervous system. Although conventional magnetic resonance imaging (MRI) is… (see more) widely used for MS diagnosis and clinical follow‐up, quantitative MRI has the potential to provide valuable intrinsic values of tissue properties that can enhance accuracy. In this study, we investigate the efficacy of diffusion MRI in distinguishing MS lesions within the cervical spinal cord, using a combination of metrics extracted from diffusion tensor imaging and Ball‐and‐Stick models.
2021-08-09
ArXiv (preprint)
doi.org
arxiv.org
Dynamic shimming in the cervical spinal cord for multi-echo gradient-echo imaging at 3 T
Eva Alonso‐Ortiz
Daniel Papp
Alain D’astous
Julien Cohen-Adad
2021-07-21
ArXiv (preprint)
doi.org
arxiv.org
Rapid simultaneous acquisition of macromolecular tissue volume, susceptibility, and relaxometry maps
Fang Frank Yu
Susie Y. Huang
T. Witzel
Ashwin S. 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… (see more) 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.
2021-06-09
bioRxiv (preprint)
doi.org