Revailler, W.; Cottereau, A.S.; Rossi, C.; Noyelle, R.; Trouillard, T.; Morschhauser, F.; Casasnovas, O.; Thieblemont, C.; Gouill, S.L.; André, M.;
et al. Deep Learning Approach to Automatize TMTV Calculations Regardless of Segmentation Methodology for Major FDG-Avid Lymphomas. Diagnostics 2022, 12, 417.
https://doi.org/10.3390/diagnostics12020417
AMA Style
Revailler W, Cottereau AS, Rossi C, Noyelle R, Trouillard T, Morschhauser F, Casasnovas O, Thieblemont C, Gouill SL, André M,
et al. Deep Learning Approach to Automatize TMTV Calculations Regardless of Segmentation Methodology for Major FDG-Avid Lymphomas. Diagnostics. 2022; 12(2):417.
https://doi.org/10.3390/diagnostics12020417
Chicago/Turabian Style
Revailler, Wendy, Anne Ségolène Cottereau, Cedric Rossi, Rudy Noyelle, Thomas Trouillard, Franck Morschhauser, Olivier Casasnovas, Catherine Thieblemont, Steven Le Gouill, Marc André,
and et al. 2022. "Deep Learning Approach to Automatize TMTV Calculations Regardless of Segmentation Methodology for Major FDG-Avid Lymphomas" Diagnostics 12, no. 2: 417.
https://doi.org/10.3390/diagnostics12020417
APA Style
Revailler, W., Cottereau, A. S., Rossi, C., Noyelle, R., Trouillard, T., Morschhauser, F., Casasnovas, O., Thieblemont, C., Gouill, S. L., André, M., Ghesquieres, H., Ricci, R., Meignan, M., & Kanoun, S.
(2022). Deep Learning Approach to Automatize TMTV Calculations Regardless of Segmentation Methodology for Major FDG-Avid Lymphomas. Diagnostics, 12(2), 417.
https://doi.org/10.3390/diagnostics12020417
