RTA-Former: Reverse Transformer Attention for Polyp Segmentation

arXiv:2401.11671v2 Announce Type: replace-cross
Abstract: Polyp segmentation is a key aspect of colorectal cancer prevention, enabling early detection and guiding subsequent treatments. Intelligent diagnostic tools, including deep learning solutions, are widely explored to streamline and potentially automate this process. However, even with many powerful network architectures, there still comes the problem of producing accurate edge segmentation. In this paper, we introduce a novel network, namely RTA-Former, that employs a transformer model as the encoder backbone and innovatively adapts Reverse Attention …

abstract architectures arxiv attention automate cancer cs.cv cs.lg deep learning detection diagnostic eess.iv enabling however intelligent key network prevention process segmentation solutions tools transformer transformer attention type