Accurate polyp detection is essential for the early diagnosis and effective treatment of colorectal cancer (CRC). However, colonoscopy videos in real-world clinical settings present significant challenges, often causing existing algorithms to fail. C...
BACKGROUND: CST4 is associated with various cancers but its diagnostic value in colorectal cancer (CRC) has not been clearly established. This study aims to further validate the diagnostic value of CST4 in colorectal cancer using random forest models...
Colonoscopy is the gold standard for the examination and detection of polyps, with over 90% of polyps potentially progressing into colorectal cancer. Accurate polyp segmentation plays a pivotal role in the early diagnosis and treatment of colorectal ...
OBJECTIVES: Small animal models, particularly mice, are crucial for studying gastrointestinal diseases like colorectal cancer. Tumor assessment via colonoscopy generates large video datasets, necessitating automated analysis due to limited resources ...
BACKGROUND: Artificial intelligence (AI) models are increasingly being developed to improve the efficiency of pathological diagnoses. Rapid technological advancements are leading to more widespread availability of AI models that can be used by domain...
Currently, colonoscopy stands as the most efficient approach for detecting colorectal polyps. In clinical diagnosis, colorectal cancer is closely related to colorectal polyps. Therefore, precise segmentation of polyps holds paramount importance for t...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 1, 2025
Recent advancements in deep learning techniques have contributed to developing improved polyp segmentation methods, thereby aiding in the diagnosis of colorectal cancer and facilitating automated surgery like endoscopic submucosal dissection (ESD). H...
In medical image segmentation, traditional CNN-based models excel at extracting local features but have limitations in capturing global features. Conversely, Mamba, a novel network framework, effectively captures long-range feature dependencies and e...
Accurate real-time optical diagnosis that distinguishes neoplastic from non-neoplastic colorectal lesions during colonoscopy can lower the costs of pathological assessments, prevent unnecessary polypectomies, and help avoid adverse events. Using a mu...
Colonoscopy is a crucial tool for evaluating lower gastrointestinal disease, monitoring high-risk patients for colorectal neoplasia, and screening for colorectal cancer. In the United States, over 14 million colonoscopies are performed annually, with...
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