Self-Supervised Contrastive Learning with Vision Transformers for Data-Efficient Medical Image Classification
Medical image classification often suffers from the scarcity of labeled data, which limits the performance of deep learning models. We propose a self-supervised contrastive learning framework that integrates Vision Transformers to address this data efficiency challenge. The method first applies rigorous image preproces...