A Weakly Supervised Consistency-based Learning Method for COVID-19 Segmentation in CT Images. Laradji, I. H., Rodríguez, P., Mañas, O., Lensink, K., Law, M., Kurzman, L., Parker, W., Vázquez, D., & Nowrouzezahrai, D. In IEEE Winter Conference on Applications of Computer Vision, WACV 2021, Waikoloa, HI, USA, January 3-8, 2021, pages 2452–2461, 2021. IEEE.
Paper doi bibtex @inproceedings{DBLP:conf/wacv/LaradjiRMLLKP0N21,
author = {Issam H. Laradji and
Pau Rodr{\'{\i}}guez and
Oscar Ma{\~{n}}as and
Keegan Lensink and
Marco Law and
Lironne Kurzman and
William Parker and
David V{\'{a}}zquez and
Derek Nowrouzezahrai},
title = {A Weakly Supervised Consistency-based Learning Method for {COVID-19}
Segmentation in {CT} Images},
booktitle = {{IEEE} Winter Conference on Applications of Computer Vision, {WACV}
2021, Waikoloa, HI, USA, January 3-8, 2021},
pages = {2452--2461},
publisher = {{IEEE}},
year = {2021},
url = {https://doi.org/10.1109/WACV48630.2021.00250},
doi = {10.1109/WACV48630.2021.00250},
timestamp = {Wed, 07 Dec 2022 00:00:00 +0100},
biburl = {https://dblp.org/rec/conf/wacv/LaradjiRMLLKP0N21.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}