Rachid Zeghlache, Pierre-Henri Conze, Mostafa El Habib Daho, Yihao Li, Hugo Le Boité, Ramin Tadayoni, Pascale Massin, Béatrice Cochener, Ikram Brahim, Gwenolé Quellec, Mathieu Lamard. LMT: Longitudinal Mixing Training, a Framework to Predict Disease Progression from a Single Image. In Xiaohuan Cao, Xuanang Xu, Islem Rekik, Zhiming Cui, Xi Ouyang, editors, Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings, Part II. Volume 14349 of Lecture Notes in Computer Science, pages 22-32, Springer, 2023. [doi]
@inproceedings{ZeghlacheCDLBTMCBQL23-0,
title = {LMT: Longitudinal Mixing Training, a Framework to Predict Disease Progression from a Single Image},
author = {Rachid Zeghlache and Pierre-Henri Conze and Mostafa El Habib Daho and Yihao Li and Hugo Le Boité and Ramin Tadayoni and Pascale Massin and Béatrice Cochener and Ikram Brahim and Gwenolé Quellec and Mathieu Lamard},
year = {2023},
doi = {10.1007/978-3-031-45676-3_3},
url = {https://doi.org/10.1007/978-3-031-45676-3_3},
researchr = {https://researchr.org/publication/ZeghlacheCDLBTMCBQL23-0},
cites = {0},
citedby = {0},
pages = {22-32},
booktitle = {Machine Learning in Medical Imaging - 14th International Workshop, MLMI 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings, Part II},
editor = {Xiaohuan Cao and Xuanang Xu and Islem Rekik and Zhiming Cui and Xi Ouyang},
volume = {14349},
series = {Lecture Notes in Computer Science},
publisher = {Springer},
isbn = {978-3-031-45676-3},
}