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Colonic Polyps

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Enhancing polyp classification: A comparative analysis of spatio-temporal techniques.

Medical engineering & physics
Colorectal cancer (CRC) is a major health concern, ranking as the third deadliest cancer globally. Early diagnosis of adenomatous polyps which are pre-cancerous abnormal tissue growth, is crucial for preventing CRC. Artificial intelligence-assisted n...

Role of Artificial Intelligence for Colon Polyp Detection and Diagnosis and Colon Cancer.

Gastrointestinal endoscopy clinics of North America
The broad use of artificial intelligence (AI) and its various applications have already shown significant impact in medicine and in everyday life. In gastroenterology, the most studied AI tools at present are computer-aided detection (CADe) and compu...

Application of an Automated Deep Learning Program to A Diagnostic Classification Model: Differentiating High-Risk Adenomas Among Colorectal Polyps 10 mm or Smaller.

Journal of digestive diseases
OBJECTIVE: This study aimed to develop a computer-aided diagnosis (CADx) model using an automated deep learning (DL) program to classify low- and high-risk adenomas among colorectal polyps ≤ 10 mm with standard white-light endoscopy.

PFPRNet: A Phase-Wise Feature Pyramid With Retention Network for Polyp Segmentation.

IEEE journal of biomedical and health informatics
Early detection of colonic polyps is crucial for the prevention and diagnosis of colorectal cancer. Currently, deep learning-based polyp segmentation methods have become mainstream and achieved remarkable results. Acquiring a large number of labeled ...

A Novel Natural Language Processing Tool Improves Colonoscopy Auditing of Adenoma and Serrated Polyp Detection Rates.

Journal of gastroenterology and hepatology
BACKGROUND AND STUDY AIMS: Determining adenoma detection rate (ADR) and serrated polyp detection rate (SDR) can be challenging as they usually involve manual matching of colonoscopy and histology reports. This study aimed to validate a Natural Langua...

Construction and validation of machine learning-based predictive model for colorectal polyp recurrence one year after endoscopic mucosal resection.

World journal of gastroenterology
BACKGROUND: Colorectal polyps are precancerous diseases of colorectal cancer. Early detection and resection of colorectal polyps can effectively reduce the mortality of colorectal cancer. Endoscopic mucosal resection (EMR) is a common polypectomy pro...

[Role of Artificial Intelligence in Improving Quality of Colonoscopy].

The Korean journal of gastroenterology = Taehan Sohwagi Hakhoe chi
Colorectal cancer is a common malignancy and a major health concern in Korea. Although colonoscopy is an effective tool for screening and preventing colorectal cancer through the early detection of pre-cancerous lesions, many factors influence the qu...

DCATNet: polyp segmentation with deformable convolution and contextual-aware attention network.

BMC medical imaging
Polyp segmentation is crucial in computer-aided diagnosis but remains challenging due to the complexity of medical images and anatomical variations. Current state-of-the-art methods struggle with accurate polyp segmentation due to the variability in ...

EFCNet enhances the efficiency of segmenting clinically significant small medical objects.

Scientific reports
Efficient segmentation of small hyperreflective dots, key biomarkers for diseases like macular edema, is critical for diagnosis and treatment monitoring.However, existing models, including Convolutional Neural Networks (CNNs) and Transformers, strugg...

Boosting polyp screening with improved point-teacher weakly semi-supervised.

Computers in biology and medicine
Polyps, like a silent time bomb in the gut, are always lurking and can explode into deadly colorectal cancer at any time. Many methods are attempted to maximize the early detection of colon polyps by screening, however, there are still face some chal...