Polyp image segmentation using deep learning techniques: ResUnet++ architecture

This study presents a novel polyp segmentation approach using ResUnet++. Trained on Kvasir-SEG and CVCClinicDB, ResUnet++ significantly outperforms traditional UNet and ResUnet. Its residual blocks and attention mechanisms enhance feature extraction, leading to improved segmentation in challenging cases.