Discriminative Feature Learning for Lacune Detection in 2D T2‐FLAIR Images using Supervised Contrastive Learning

This study introduces a deep-learning based approach for detecting lacunes from highly imbalanced dataset using encoder pretrained with supervised contrastive learning. Future work will focus on expanding the current approach to include lacune localization within specific brain regions and conducting external validation across multiple centers.