Distilling Foundation Models for Lightweight Polyp Segmentation

This research explores a practical approach to reduce the computational demands of medical image segmentation models by distilling knowledge from larger foundation models. The study's focus on polyp segmentation has direct implications for improving diagnostic accuracy and efficiency in medical image analysis.