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Julien Cohen-Adad
Phd (Paris/Montreal), MSc (Rennes), Eng (Paris)
Student research project(s)

Research interests and affiliations

Research interests

My lab is developing advanced Magnetic Resonance Imaging (MRI) techniques for quantitative assessment of the brain and spinal cord structure. These developments include hardware (coils), MRI sequences (relaxometry, diffusion tensor imaging, magnetization transfer, functional MRI) and software (multimodal registration, segmentation, motion correction, distortion correction). There is a strong focus on translating research developments into clinics, aiming to improve the diagnosis and prognosis in patients suffering from neurological diseases and traumas. 

The environment is highly multi-disciplinary. We interact with biomedical engineers, physicists, radiologists, neurologists and neurophysiologists. Plus, our lab collaborates with the Martinos Center for Biomedical Imaging at Harvard, therefore some projects will involve travelling to Boston. Projects include:

  • Developing methods for spinal cord MRI in multiple sclerosis (collaboration with Harvard),
  • Studying features of the brain using ultra-high field MRI (collaboration with Harvard),
  • Development of deep learning methods for analysis of medical images (collaboration with Mila),
  • Development of open source software for medical imaging applications,
  • Building of MRI antenna
Expertise type(s) (NSERC subjects)
  • 1900 BIOMEDICAL ENGINEERING
  • 1901 Biomedical technology
  • 3102 Nuclear physics
  • 6400 LIFE SCIENCES RESEARCH RELATED TO HUMAN HEALTH AND DISEASE
  • 9000 MEDICAL SCIENCES

Publications

Recent publications
Journal article
Huang, Y.N., Meftah, E.-M., Pion, C.H., Mac-Thiong, J.-M., Cohen-Adad, J. & Barthelemy, D. (2022). Quantitative electrophysiological assessments as predictive markers of lower limb motor recovery after spinal cord injury: a pilot study with an adaptive trial design. Spinal Cord Series and Cases, 8(1), 8 pages. Retrieved from https://doi.org/10.1038/s41394-022-00491-0
Journal article
Yu, F.F., Huang, S.Y., Kumar, A., Witzel, T., Liao, C.Y., Duval, T., Cohen-Adad, J. & Bilgic, B. (2022). Rapid simultaneous acquisition of macromolecular tissue volume, susceptibility, and relaxometry maps. Magnetic Resonance in Medicine, 87(2), 781-790. Retrieved from https://doi.org/10.1002/mrm.28995
Journal article
Yu, F.F., Huang, S.Y., Kumar, A., Witzel, T., Liao, C., Duval, T., Cohen-Adad, J. & Bilgic, B. (2022). Rapid simultaneous acquisition of macromolecular tissue volume, susceptibility, and relaxometry maps (vol 87, pg 781, 2022). Magnetic Resonance in Medicine, 87(6), 3022-3023. Retrieved from https://doi.org/10.1002/mrm.29158
Journal article
Wong, A.L., Hricz, N., Malapati, H., von Guionneau, N., Wong, M., Harris, T., Boudreau, M., Cohen-Adad, J. & Tuffaha, S. (2021). A simple and robust method for automating analysis of naive and regenerating peripheral nerves. Plos One, 16(7), 14 pages. Retrieved from https://doi.org/10.1371/journal.pone.0248323

Biography

Prof. Cohen-Adad is an MR physicist and software developer with over 15 years of experience in advanced MRI methods for quantitative assessment of the brain and spinal cord structure and function. He is an associate professor at Polytechnique Montreal, adjunct professor of neuroscience at the University of Montreal, associate director of the Neuroimaging Functional Unit (Univ. Montreal), member of Mila (Univ. Montreal) and he holds the Canada Research Chair in Quantitative Magnetic Resonance Imaging. Along with his colleague Prof. Nikola Stikov, he is directing the NeuroPoly Lab (www.neuro.polymtl.ca), which includes about 20 graduate students and research associates. Prof. Cohen-Adad's research is highly cited (Google Scholar). As a leader in the field, he organized multiple workshops at international conferences (https://spinalcordmri.org/workshops.html). He is a frequent guest lecturer on advanced MRI methods and he regularly serves as consultant for various companies (e.g. Biospective Inc., NeuroRx, IMEKA) and academic (Harvard, U. Toronto, UCL, UCSF, etc.) for setting up MRI acquisition and image processing protocols. 

Do you want to join the lab? See: job opportunities

Teaching

  • GBM6125
  • GBM6904/7904
  • GBM8378

Supervision at Polytechnique

COMPLETED

  • Ph.D. Thesis (4)

    • Mangeat, G. (2021). Development of in-Vivo Histology with Quantitative Magnetic Resonance Imaging to Resolve Fine Neurodegenerative Features (Ph.D. Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/6280/
    • De Leener, B. (2017). Development of an MRI template and analysis pipeline for the spinal cord and application in patients with spinal cord injury (Ph.D. Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2743/
    • Duval, T. (2017). Quantification de la microstructure de la moelle épinière humaine par IRM et application chez des patients avec sclérose en plaques (Ph.D. Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2871/
    • Lopez Rios, N. (2017). Development of a New Multi-Channel MRI Coil Optimized for Brain Studies in Human Neonates (Ph.D. Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2816/
  • Master's Thesis (13)

    • Vincent, O. (2021). Impact of Rater Style on Deep Learning Segmentation in Medical Imaging (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/6283/
    • Rouhier, L. (2020). Prognosis for Degenerative Cervical Myelopathy: A Computer Learning Approach on the AOspine Database (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/5348/
    • Nami, H. (2019). Clustering of the White Matter Tracts in the Rat Spinal Cord Based on Quantitative Histology (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/4009/
    • Samuel Perone, C. (2019). Deep Learning Methods for MRI Spinal Cord Gray Matter Segmentation (Master's Thesis, Polytechnique Montréal). Retrieved from https://publications.polymtl.ca/3811/
    • Gros, C. (2018). Automatic Segmentation of Intramedullary Multiple Sclerosis Lesions (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/3200/
    • Zaimi, A. (2018). Automatic axon and myelin segmentation of microscopy images and morphometrics extraction (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/3089/
    • Germain, G. (2017). Une antenne hybride RF/shimming pour l'IRM de la moelle épinière (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2623/
    • Saliani, A. (2017). Construction d'un atlas de la microstructure de la matière blanche de la moelle épinière chez le rat à partir d'acquisitions histologiques (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2734/
    • Vuong, M.T. (2017). Comparison of Myelin Imaging Techniques in Ex Vivo Spinal Cord (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2683/
    • Lévy, S. (2016). Caractérisation de la microstructure des voies spinales humaines par IRM multiparamétrique (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2068/
    • Mangeat, G. (2016). Study of Human Cortical Microstructure Using Magnetization Transfer and T2* Mapping with Application in Multiple Sclerosis (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2079/
    • Foias, A. (2015). Design and Construction of a Highly Sensitive Coil for MRI of the Spinal Cord (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/2001/
    • De Leener, B. (2014). Segmentation automatique de la moelle épinière sur des images de résonance magnétique par propagation de modèles déformables (Master's Thesis, École Polytechnique de Montréal). Retrieved from https://publications.polymtl.ca/1471

News about Julien Cohen-Adad

NEWS | January 6, 2022
Québec Science Discovery of the Year: two Polytechnique Montréal professors among the top10 finalists | Read
BLOG | August 31, 2021
Giant leaps forward in spinal cord imaging | Read
NEWS | June 22, 2021
Canada Research Chairs Program: Chair renewal for Polytechnique Montréal's Professor Julien Cohen-Adad | Read
NEWS | February 24, 2021
50 Polytechnique Montréal researchers among the top 2% most cited in their respective fields | Read

Press review about Julien Cohen-Adad

January 23, 2022, Québec Science, Un nouveau protocole qui promet de changer le monde médical Une équipe de 92 personnes, menée par le Pr Julien Cohen-Adad du Département de génie électrique de Polytechnique Montréal, a mis au point un protocole permettant de créer des images par résonance magnétique de la moelle épinière plus claires et plus justes qu’auparavant.
January 1, 2022, Québec Science, Moelle épinière : nouveau souffle pour les IRM Jusqu’à tout récemment, les images de la moelle épinière obtenues par résonance magnétique n’étaient pas standardisées, ce qui empêchait de les comparer et de suivre l’évolution des lésions. C’est maintenant réglé grâce à une avancée du Pr Julien Cohen-Adad du Département de génie électrique sélectionnée parmi les 10 Découvertes de l’année par le magazine Québec Science.
February 8, 2016, Le Devoir, Les capacités d'apprentissage du système nerveux Image obtenue par résonance magnétique des faisceaux de fibres nerveuses (ou axones) qui descendent dans la moelle épinière et dont les corps cellulaires sont situés dans le cortex cérébral. ( Photo: Laboratoire du professeur Julien Cohen-Adad, École Polytechnique de Montréal).