Open-source pipeline for multi-class segmentation of the spinal cord with deep learning

François Paugam, Jennifer Lefeuvre, Christian S. Perone, Charley Gros, Daniel S. Reich, Pascal Sati and Julien Cohen-Adad

Article (2019)

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Department:	Department of Electrical Engineering Institut de génie biomédical
Research Center:	NeuroPoly - Laboratoire de Recherche en Neuroimagerie
PolyPublie URL:	https://publications.polymtl.ca/44620/
Journal Title:	Magnetic Resonance Imaging (vol. 64)
Publisher:	Elsevier
DOI:	10.1016/j.mri.2019.04.009
Official URL:	https://doi.org/10.1016/j.mri.2019.04.009
Date Deposited:	18 Apr 2023 15:02
Last Modified:	25 Sep 2024 16:32

Cite in APA 7:	Paugam, F., Lefeuvre, J., Perone, C. S., Gros, C., Reich, D. S., Sati, P., & Cohen-Adad, J. (2019). Open-source pipeline for multi-class segmentation of the spinal cord with deep learning. Magnetic Resonance Imaging, 64, 21-27. https://doi.org/10.1016/j.mri.2019.04.009
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