2 papers
cs.CV2026
Beyond the Encoder: Joint Encoder-Decoder Contrastive Pre-Training Improves Dense Prediction
Sébastien Quetin, Tapotosh Ghosh, Farhad Maleki
Contrastive learning methods in self-supervised settings have primarily focused on pre-training encoders, while decoders are typically introduced and trained separately for downstr…
eess.IV2025
Automatic segmentation of Organs at Risk in Head and Neck cancer patients from CT and MRI scans
Sébastien Quetin, Andrew Heschl, Mauricio Murillo +5
Purpose: To present a high-performing, robust, and flexible deep learning pipeline for automatic segmentation of 30 organs-at-risk (OARs) in head and neck (H&N) cancer patients, us…