R. Zeghlach and al. (2024)
Medical Image Computing and Computer Assisted Intervention .MICCAI 2024.
Type: Oral communication
“LMT: Longitudinal Mixing Training, a framework to predict disease progression from a single image.”
R. Zeghlache and al.
Machine Learning in Medical Imaging. MLMI 2023. Lecture Notes in Computer Science, vol 14349. Springer, Cham.
“Longitudinal self-supervised learning using neural ordinary differential equation”
R. Zeghlache and al.
Predictive Intelligence in Medicine. PRIME 2023.October 8,2023 Lecture Notes in Computer Science, vol 14277. Springer, Cham.
“Improved Automatic Diabetic Retinopathy Severity Classification Using Deep Multimodal Fusion of UWF-CFP and OCTA Images”
M. El Habib Daho, et al.
“Ophthalmic Medical Image Analysis” . OMIA 2023. Lecture Notes in Computer Science, vol 14096. Springer, Cham.
https://doi.org/10.1007/978-3-031-44013-7_2
“Multimodal Information Fusion for Glaucoma and Diabetic Retinopathy Classification”
Y.Li and al.
Ophthalmic Medical Image Analysis, Singapore, Singapore, Sep. 2022, pp. 53–62.
https://doi.org/10.1007/978-3-031-16525-2_6
“Detection of Diabetic Retinopathy Using Longitudinal Self-supervised Learning,”
R.Zeghlache et al.
in Ophthalmic Medical Image Analysis, Singapore, Singapore, Sep. 2022, pp. 43–52.
https://doi.org/10.1007/978-3-031-16525-2_5
