François Paugam, Jennifer Lefeuvre, Christian S. Perone, Charley Gros, Daniel S. Reich, Pascal Sati and Julien Cohen-Adad
Article (2019)
An external link is available for this item| 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: | 08 Apr 2025 07:10 |
| 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 |
|---|---|
Statistics
Dimensions
