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 …
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 …
Irv2-net: A deep learning framework for enhanced polyp segmentation performance integrating inceptionresnetv2 and unet architecture with test time augmentation …
Colorectal polyps in the colon or rectum are precancerous growths that can lead to a more
severe disease called colorectal cancer. Accurate segmentation of polyps using medical …
severe disease called colorectal cancer. Accurate segmentation of polyps using medical …
[HTML][HTML] Know your orientation: A viewpoint-aware framework for polyp segmentation
Automatic polyp segmentation in endoscopic images is critical for the early diagnosis of
colorectal cancer. Despite the availability of powerful segmentation models, two challenges …
colorectal cancer. Despite the availability of powerful segmentation models, two challenges …
[HTML][HTML] Multi-scale and multi-path cascaded convolutional network for semantic segmentation of colorectal polyps
Colorectal polyps are structural abnormalities of the gastrointestinal tract that can potentially
become cancerous in some cases. The study introduces a novel framework for colorectal …
become cancerous in some cases. The study introduces a novel framework for colorectal …
ControlPolypNet: Towards Controlled Colon Polyp Synthesis for Improved Polyp Segmentation
In recent years generative models have been very popular in medical imaging applications
because they generate realistic-looking synthetic images which is crucial for the medical …
because they generate realistic-looking synthetic images which is crucial for the medical …
Polyp sam 2: Advancing zero shot polyp segmentation in colorectal cancer detection
Polyp segmentation plays a crucial role in the early detection and diagnosis of colorectal
cancer. However, obtaining accurate segmentations often requires labor-intensive …
cancer. However, obtaining accurate segmentations often requires labor-intensive …
Frequency-based federated domain generalization for polyp segmentation
Federated Learning (FL) offers a powerful strategy for training machine learning models
across decentralized datasets while maintaining data privacy, yet domain shifts among …
across decentralized datasets while maintaining data privacy, yet domain shifts among …
Free Meal: Boosting Semi-Supervised Polyp Segmentation by Harvesting Negative Samples
Existing semi-supervised polyp segmentation methods assume that unlabeled images are
positive, containing lesions to be annotated, while neglecting negative samples that are …
positive, containing lesions to be annotated, while neglecting negative samples that are …
Edge-guided multi-scale adaptive feature fusion network for liver tumor segmentation
T Zhang, Y Liu, Q Zhao, G Xue, H Shen - Scientific Reports, 2024 - nature.com
Automated segmentation of liver tumors on CT scans is essential for aiding diagnosis and
assessing treatment. Computer-aided diagnosis can reduce the costs and errors associated …
assessing treatment. Computer-aided diagnosis can reduce the costs and errors associated …