Researcher

    Benjamin De Leener , Ph.D. , Ing.

    benjamin.de-leener@polymtl.ca
    Benjamin De Leener
    Research Axis
    Musculoskeletal Health, Rehabilitation and Medical Technologies Axis
    Research Theme
    Neurodevelopmental diseases

    Phone
    514-340-4711, ext.3689

    Online

    Title

    Laboratory

    Research Laboratory for Magnetic Resonance Imaging in Children (MAGIC lab)

    Education

    • Postdoctoral fellow, Montreal Neurological Institute, McGill University, Montreal, Canada, 2018-2019
    • Postdoctoral fellow, Department of Electrical Engineering, Polytechnique Montreal, Montreal, Canada, 2017-2018
    • Ph.D., Biomedical Engineering, Polytechnique Montreal, Montreal, Canada, 2014-2017
    • M.Sc.A. Biomedical Engineering, Polytechnique Montreal, Montreal, Canada, 2012-2014
    • M.Sc.A., Biomedical Engineering, Université Libre de Bruxelles, Bruxelles, Belgique, 2011-2014
    • B. Ing., Biomedical Engineering, Université Libre de Bruxelles, Bruxelles, Belgique, 2007-2011

    Research Interests

    • Medical imaging
    • Computer vision
    • Pediatric neuroimaging
    • Image processing and analysis
    • Machine learning
    • Modelisation

    NSERC subjects

    • 1901 Biomedical technology
    • 2603 Computer vision
    • 2605 Pattern analysis and machine intelligence
    • 2604 Intelligent systems applications
    • 2708 Image and video processing

    Career Summary

    My research interests pertain to the development of new technologies in pediatric neuroimaging. More particularly, my research lab focuses on developing open-source software for analyzing brain and spinal cord images acquired with magnetic resonance imaging, using advanced segmentation and registration approaches using machine learning and neurodevelopmental templates and atlases. The MAGIC research lab is closely linked to the TransMedTech institute, Polytechnique Montreal and the Research Center of the Sainte-Justine University Hospital, enabling strong collaborations between researchers, engineers, psychologists, radiologists, and clinicians.

    Awards and Distinctions

    • TransMedTech Institute Chair in Computer Engineering, 2019-2021
    • Postdoctoral fellowship, HBHL, 2018-2019
    • Ph.D. scholarship, FRQNT, 2016-2017
    • « Star » research-student from FRQNT, 2016

    Major Financing

    • TransMedTech Institute Chair in Computer Engineering

    Presentations

    • De Leener B, Solstrand Dahlberg L, Khatibi A, Cohen-Adad J, Doyon J. Effect of non-protonated perfluorocarbon liquid-filled SatPadsTM on spinal cord MR imaging. Proceedings of the 28th Annual Meeting of ISMRM, Sydney, Australia. 2020.
    • De Leener B, Solstrand Dahlberg L, Khatibi A, Kinany N, Doyon J. Improving spatial normalization of functional MRI data of the spinal cord using cerebrospinal fluid segmentation. Proceedings of the 28th Annual Meeting of ISMRM, Sydney, Australia. 2020.
    • Ouellette R, Treaba CA, Granberg T, Barletta V, Herranz E, Mangeat G, et al. Characterization of multiple sclerosis grey and white matter pathology in the brain and spinal cord at 7 Tesla MRI. ECTRIMS 2018. 2018.
    • Shahrampour S, De Leener B, Middelton D, Flanders A, Faro S, Cohen-Adad J, et al. Volumetric Analysis of Pediatric Spinal Cord Structural MRI data using SCT. Proceedings of the 56th Annual Meeting and the ASNR Symposium 2018. 2018. p. O433.
    • De Leener B, Fonov V, Collins DL, Callot V, Stikov N, Cohen-Adad J. PAM50: Multimodal template of the brainstem and spinal cord compatible with the ICBM152 space. Proceedings of the 25th Annual Meeting of ISMRM, Honolulu, USA. 2017.

    Selected Publications

    Complete list of publications.

    • Eden D, Gros C, Badji A, Dupont SM, De Leener B, Maranzano J, et al. Spatial distribution of multiple sclerosis lesions in the cervical spinal cord. Brain. 2019;142: 633–646. doi:10.1093/brain/awy352
    • Gros C, De Leener B, Badji A, Maranzano J, Eden D, Dupont SM, et al. Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks. Neuroimage. arxiv.org; 2019;184: 901–915. doi:10.1016/j.neuroimage.2018.09.081
    • Martin AR, De Leener B, Cohen-Adad J, Kalsi-Ryan S, Cadotte DW, Wilson JR, et al. Monitoring for myelopathic progression with multiparametric quantitative MRI. PLoS One. 2018;13: e0195733. doi:10.1371/journal.pone.0195733
    • De Leener B, Fonov VS, Collins DL, Callot V, Stikov N, Cohen-Adad J. PAM50: Unbiased multimodal template of the brainstem and spinal cord aligned with the ICBM152 space. Neuroimage. 2018;165: 170–179. doi:10.1016/j.neuroimage.2017.10.041
    • Gros C, De Leener B, Dupont SM, Martin AR, Fehlings MG, Bakshi R, et al. Automatic spinal cord localization, robust to MRI contrasts using global curve optimization. Med Image Anal. 2017;44: 215–227. doi:10.1016/j.media.2017.12.001
    • Prados F, Ashburner J, Blaiotta C, Brosch T, Carballido-Gamio J, Cardoso MJ, et al. Spinal cord grey matter segmentation challenge. Neuroimage. 2017;152: 312–329. doi:10.1016/j.neuroimage.2017.03.010
    • De Leener B, Mangeat G, Dupont S, Martin AR, Callot V, Stikov N, et al. Topologically preserving straightening of spinal cord MRI. J Magn Reson Imaging. 2017; doi:10.1002/jmri.25622
    • Martin AR, De Leener B, Cohen-Adad J, Cadotte DW, Kalsi-Ryan S, Lange SF, et al. Clinically Feasible Microstructural MRI to Quantify Cervical Spinal Cord Tissue Injury Using DTI, MT, and T2*-Weighted Imaging: Assessment of Normative Data and Reliability. AJNR Am J Neuroradiol. 2017;38: 1257–1265. doi:10.3174/ajnr.A5163
    • Martin AR, De Leener B, Cohen-Adad J, Cadotte DW, Kalsi-Ryan S, Lange SF, et al. A Novel MRI Biomarker of Spinal Cord White Matter Injury: T2*-Weighted White Matter to Gray Matter Signal Intensity Ratio. AJNR Am J Neuroradiol. 2017;38: 1266–1273. doi:10.3174/ajnr.A5162
    • De Leener B, Lévy S, Dupont SM, Fonov VS, Stikov N, Louis Collins D, et al. SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data. Neuroimage. 2017;145: 24–43. doi:10.1016/j.neuroimage.2016.10.009
 

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