Stepwise feature fusion: Local guides global
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 …
is necessary for early screening and prevention of colorectal cancer. However, due to the …
Colonformer: An efficient transformer based method for colon polyp segmentation
Identifying polyps is challenging for automatic analysis of endoscopic images in computer-
aided clinical support systems. Models based on convolutional networks (CNN) …
aided clinical support systems. Models based on convolutional networks (CNN) …
[HTML][HTML] Generalist vision foundation models for medical imaging: A case study of segment anything model on zero-shot medical segmentation
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 …
examine the recent Segment Anything Model (SAM) on medical images, and report both …
[HTML][HTML] FCN-transformer feature fusion for polyp segmentation
E Sanderson, BJ Matuszewski - Annual conference on medical image …, 2022 - Springer
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 …
colorectal cancer (CRC). Segmentation is valuable for two significant clinical applications …
Attention mechanisms in medical image segmentation: A survey
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 …
mechanisms that distinguish important parts from irrelevant parts have been widely used in …
META-Unet: Multi-scale efficient transformer attention Unet for fast and high-accuracy polyp segmentation
H Wu, Z Zhao, Z Wang - IEEE Transactions on Automation …, 2023 - ieeexplore.ieee.org
Polyp segmentation plays an important role in preventing Colorectal cancer. Although Vision
Transformer has been widely introduced in medical image segmentation to compensate the …
Transformer has been widely introduced in medical image segmentation to compensate the …
CAFE-Net: Cross-attention and feature exploration network for polyp segmentation
G Liu, S Yao, D Liu, B Chang, Z Chen, J Wang… - Expert Systems with …, 2024 - Elsevier
Colorectal polyp segmentation can help physicians screen colonoscopy images, which is
essential for preventing colorectal cancer. The segmentation of polyps encounters multiple …
essential for preventing colorectal cancer. The segmentation of polyps encounters multiple …
G-CASCADE: Efficient cascaded graph convolutional decoding for 2D medical image segmentation
MM Rahman, R Marculescu - Proceedings of the IEEE/CVF …, 2024 - openaccess.thecvf.com
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 …
Cascaded Graph Convolutional Attention Decoder (G-CASCADE), for 2D medical image …
DuAT: Dual-aggregation transformer network for medical image segmentation
Transformer-based models have been widely demonstrated to be successful in computer
vision tasks by modeling long-range dependencies and capturing global representations …
vision tasks by modeling long-range dependencies and capturing global representations …
A survey on deep learning for polyp segmentation: Techniques, challenges and future trends
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 …
of colorectal cancer (CRC). Polyp segmentation provides an effective solution to assist …