Early detection and assessment of polyps play a crucial role in the prevention and treatment
of colorectal cancer (CRC). Polyp segmentation provides an effective solution to assist …

Colonoscopy, currently the most efficient and recognized colon polyp detection technology,
is necessary for early screening and prevention of colorectal cancer. However, due to the …

Medical image analysis plays an important role in clinical diagnosis. In this paper, we
examine the recent Segment Anything Model (SAM) on medical images, and report both …

Identifying polyps is challenging for automatic analysis of endoscopic images in computer-
aided clinical support systems. Models based on convolutional networks (CNN) …

Colonoscopy is widely recognised as the gold standard procedure for the early detection of
colorectal cancer (CRC). Segmentation is valuable for two significant clinical applications …

Medical image segmentation plays an important role in computer-aided diagnosis. Attention
mechanisms that distinguish important parts from irrelevant parts have been widely used in …

Polyp segmentation plays an important role in preventing Colorectal cancer. Although Vision
Transformer has been widely introduced in medical image segmentation to compensate the …

Colorectal polyp segmentation can help physicians screen colonoscopy images, which is
essential for preventing colorectal cancer. The segmentation of polyps encounters multiple …

In this paper, we are the first to propose a new graph convolution-based decoder namely,
Cascaded Graph Convolutional Attention Decoder (G-CASCADE), for 2D medical image …

Transformer-based models have been widely demonstrated to be successful in computer
vision tasks by modeling long-range dependencies and capturing global representations …