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Dimension reduction technique using a multilayered descriptor for high-precision classification of ovarian cancer tissue using optical coherence tomography: a feasibility study

Catherine St-Pierre, Wendy-Julie Madore, Étienne De Montigny, Dominique Trudel, Caroline Boudoux, Nicolas Godbout, Anne-Marie Mes-Masson, Kurosh Rahimi and Frédéric Leblond

Article (2017)

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Department: Department of Engineering Physics
PolyPublie URL: https://publications.polymtl.ca/39387/
Journal Title: Journal of Medical Imaging (vol. 4, no. 4)
Publisher: SPIE - International Society for Optical Engineering
DOI: 10.1117/1.jmi.4.4.041306
Official URL: https://doi.org/10.1117/1.jmi.4.4.041306
Date Deposited: 18 Apr 2023 15:05
Last Modified: 25 Sep 2024 16:24
Cite in APA 7: St-Pierre, C., Madore, W.-J., De Montigny, É., Trudel, D., Boudoux, C., Godbout, N., Mes-Masson, A.-M., Rahimi, K., & Leblond, F. (2017). Dimension reduction technique using a multilayered descriptor for high-precision classification of ovarian cancer tissue using optical coherence tomography: a feasibility study. Journal of Medical Imaging, 4(4), 13 pages. https://doi.org/10.1117/1.jmi.4.4.041306

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