SwinE-Net: Hybrid deep learning approach to novel polyp segmentation using convolutional neural network and Swin Transformer
Prevention of colorectal cancer (CRC) by inspecting and removing colorectal polyps has
become a global health priority because CRC is one of the most frequent cancers in the …
become a global health priority because CRC is one of the most frequent cancers in the …
[HTML][HTML] Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopy
Background Colonoscopy remains the gold-standard screening for colorectal cancer.
However, significant miss rates for polyps have been reported, particularly when there are …
However, significant miss rates for polyps have been reported, particularly when there are …
Boundary constraint network with cross layer feature integration for polyp segmentation
G Yue, W Han, B Jiang, T Zhou… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Clinically, proper polyp localization in endoscopy images plays a vital role in the follow-up
treatment (eg, surgical planning). Deep convolutional neural networks (CNNs) provide a …
treatment (eg, surgical planning). Deep convolutional neural networks (CNNs) provide a …
[HTML][HTML] Comprehensive review of publicly available colonoscopic imaging databases for artificial intelligence research: availability, accessibility, and usability
BBSL Houwen, KJ Nass, JLA Vleugels… - Gastrointestinal …, 2023 - Elsevier
Background and Aims Publicly available databases containing colonoscopic imaging data
are valuable resources for artificial intelligence (AI) research. Currently, little is known …
are valuable resources for artificial intelligence (AI) research. Currently, little is known …
Attention based multi-scale parallel network for polyp segmentation
P Song, J Li, H Fan - Computers in Biology and Medicine, 2022 - Elsevier
Colonoscopy is an effective method for detecting colorectal polyps and preventing colorectal
cancer. Therefore, in clinical practice, it is very important to accurately segment the location …
cancer. Therefore, in clinical practice, it is very important to accurately segment the location …
A survey of deep learning algorithms for colorectal polyp segmentation
S Li, Y Ren, Y Yu, Q Jiang, X He, H Li - Neurocomputing, 2024 - Elsevier
Early detecting and removing cancerous colorectal polyps can effectively reduce the risk of
colorectal cancer. Computer intelligent segmentation techniques (CIST) can improve the …
colorectal cancer. Computer intelligent segmentation techniques (CIST) can improve the …
FF-UNet: a U-shaped deep convolutional neural network for multimodal biomedical image segmentation
Automatic multimodal image segmentation is considered a challenging research area in the
biomedical field. U-shaped models have led to an enormous breakthrough in a large …
biomedical field. U-shaped models have led to an enormous breakthrough in a large …
Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge
Polyps are well-known cancer precursors identified by colonoscopy. However, variability in
their size, appearance, and location makes the detection of polyps challenging. Moreover …
their size, appearance, and location makes the detection of polyps challenging. Moreover …
CFHA-Net: A polyp segmentation method with cross-scale fusion strategy and hybrid attention
Colorectal cancer is a prevalent disease in modern times, with most cases being caused by
polyps. Therefore, the segmentation of polyps has garnered significant attention in the field …
polyps. Therefore, the segmentation of polyps has garnered significant attention in the field …
Sam2-adapter: Evaluating & adapting segment anything 2 in downstream tasks: Camouflage, shadow, medical image segmentation, and more
The advent of large models, also known as foundation models, has significantly transformed
the AI research landscape, with models like Segment Anything (SAM) achieving notable …
the AI research landscape, with models like Segment Anything (SAM) achieving notable …