De Leener, Benjamin

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Benjamin De Leener

B. Ing. (ULB), M.Sc.A. (ULB), M.Sc.A. (Poly), Ph.D. (Poly), Postdoc (McGill)

Publications

Link(s)

Assistant Professor
Department of Computer Engineering and Software Engineering

Phone: (514) 340-4711 Ext. 3689 Fax: (514) 340-5139 Room: L-5618

benjamin.de-leener@polymtl.ca

Areas of expertise
Biomedical technology Pattern analysis and machine intelligence Intelligent systems applications Computer vision Image and video processing Digital signal processing Life sciences research related to human health and disease Medical sciences Instrumentation and measurements Artificial intelligence

Primary sphere of excellence in research
Human Health

Secondary sphere(s) of excellence in research
Modeling and Artificial Intelligence Information and Communication Technologies

Research interests and affiliations

Research interests

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 laboratory is closely linked to the TransMedTech institute and the Research Center of the Sainte-Justine University Hospital, enabling strong collaborations between researchers, engineers, psychologists, radiologists, and clinicians.

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

Affiliation(s)

TransMedTech Research Chair in Pediatric Neuroimaging, Chairholder
Neuroimaging Research Laboratory (NeuroPoly), Co-director
Research Center of the Sainte-Justine University Hospital, Researcher
Unifying Neuroscience and Artificial Intelligence - Québec (UNIQUE), Member
Research Group on Globalisation and Management of Technology (GMT), Member
Institut de génie biomédical, Member

Expertise type(s) (NSERC subjects)

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

Publications

Recent publications

Landelle, C., Kinany, N., De Leener, B., Murphy, N. D., Lungu, O., Marchand‐Pauvert, V., Van De Ville, D., & Doyon, J. (2024). Cerebro-spinal somatotopic organization uncovered through functional connectivity mapping. Imaging Neuroscience, 2, 1-14.

Dimitrijevic, A., Noblet, V., & De Leener, B. (2024). Impact of Initialization on Intra-subject Pediatric Brain MR Image Registration: A Comparative Analysis between SyN ANTs and Deep Learning-Based Approaches. The Journal of Machine Learning for Biomedical Imaging, 2(Special), 916-954.

Wesselink, E. O., Pool-Goudzwaard, A., De Leener, B., Law, C. S. W., Fenyo, M. B., Ello, G. M., Coppieters, M. W., Elliott, J. M., Mackey, S., & Weber, K. A. (2024). Investigating the associations between lumbar paraspinal muscle health and age, BMI, sex, physical activity and back pain using an automated computer-vision model : a UK biobank study. Spine Journal, 24(7), 1253-1266.

Weber, K. A., Wesselink, E. O., Gutierrez, J. M., Law, C. S., Mackey, S., Ratliff, J. K., Hu, S., Chaudhari, A., Pool‐Goudzwaard, A., Coppieters, M. W., Elliott, J. M., Hancock, M. J., & De Leener, B. (2024). Three-dimensional spatial distribution of lumbar paraspinal intramuscular fat revealed by spatial parametric mapping. European Spine Journal, 9 pages.

See all publications (84)

Teaching

INF1005D – Programmation procédurale en Python

INF1007 - Introduction à la programmation

GBM8770 - Traitement numérique d'images médicales

GBM6953B - Innovation en génie biomédical

Education

Ph.D. in biomedical engineering, Polytechnique Montréal, Canada
Master in biomedical engineering, Polytechnique Montréal, Canada
Master in biomedical engineering, Université Libre de Bruxelles, Belgium
Bachelor in civil engineering, Université Libre de Bruxelles, Belgium

Supervision at Polytechnique

IN PROGRESS

Ph.D. (4)
- Zhang, Erjun. Diffusion MRI Model for Impacts Quantification of Hypoglycemia on Preterm Baby Brain.
- Dimitrijevic, Andjela. Normative Modeling of Pediatric Brain Magnetic Resonance Images for Neurodevelopmental Trajectory Characterization.
- St-Onge, Samuelle. Quantifying Neurodevelopment and Neurodegeneration in Spinal Cord Microstructure through quantitative MRI, diffusion MRI and QSM imaging.
- Ridani, Daniel. Developing and validating susceptibility-separation algorithms for the brain and spinal cord.
Master (thesis) (5)
- Chatelier, Fedwin. Development of an algorithm for neuropathological states classification.
- Tibi, Adrien. From brain tumor MRIs to intracerebral hematoma CTs: cross-modality and cross-disease domain adaptation for multiclass self-supervised segmentation.
- Banerjee, Rohan. Development of automated segmentation for spinal cord fMRI data.
- Aumais-Boucher, Étienne. Development of an application for neurological states monitoring.
- El Hachem, Antoine. Development of a multi-orientation platform for neonatal brain MRI.

COMPLETED

Master's Thesis (4)
- Fartoumi, S. (2024). Vers l'utilisation de l'apprentissage profond aux soins intensifs pour assister la prise en charge de patients ayant subi un traumatisme crânio-cérébral sévère [Master's thesis, Polytechnique Montréal].
- Ducros-Chabot, N. (2023). Développement d'un protocole d'acquisition et de reconstruction multi-orientation pour la cartographie quantitative de la susceptibilité (QSM) : vers une précision cliniquement accessible [Master's thesis, Polytechnique Montréal].
- Ridani, D. (2023). Performance of Background Field Removal and Dipole Inversion Methods to Reconstruct Brain Quantitative Susceptibility Mapping (QSM) Data Acquired in Neonatal Asphyxia [Master's thesis, Polytechnique Montréal].
- Blanc, C. (2022). Développement d'un outil de segmentation de la moelle épinière adapté à une population pédiatrique [Master's thesis, Polytechnique Montréal].

Press review about Benjamin De Leener

March 1, 2021, La Presse, ChrysaLabs : du génie biomédical aux sondes d’analyse du sol Gabriel Mangeat, étudiant au doctorat en génie biomédical, et Benjamin De Leener, professeur adjoint au Département de génie informatique et génie logiciel, tous deux à Polytechnique Montréal, qui ont fondé ChrysaLabs, parlent de la mise en marché d'une sonde portative pour analyser le sol en temps réel.

March 10, 2020, McGill, Neural Pathways: Dr. Benjamin De Leener Article sur Benjamin De Leener, professeur adjoint au Département de génie informatique et génie logiciel de Polytechnique Montréal et titulaire de la chaire de recherche TransMedTech.

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