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Dynamic Contextual Attention Network: Transforming Spatial Representations into Adaptive Insights for Endoscopic Polyp Diagnosis

Published: April 28, 2025 | arXiv ID: 2504.20306v1

By: Teja Krishna Cherukuri , Nagur Shareef Shaik , Sribhuvan Reddy Yellu and more

Potential Business Impact:

Helps doctors find hidden cancer signs earlier.

Business Areas:
Image Recognition Data and Analytics, Software

Colorectal polyps are key indicators for early detection of colorectal cancer. However, traditional endoscopic imaging often struggles with accurate polyp localization and lacks comprehensive contextual awareness, which can limit the explainability of diagnoses. To address these issues, we propose the Dynamic Contextual Attention Network (DCAN). This novel approach transforms spatial representations into adaptive contextual insights, using an attention mechanism that enhances focus on critical polyp regions without explicit localization modules. By integrating contextual awareness into the classification process, DCAN improves decision interpretability and overall diagnostic performance. This advancement in imaging could lead to more reliable colorectal cancer detection, enabling better patient outcomes.

Country of Origin
🇺🇸 United States

Page Count
6 pages

Category
Computer Science:
CV and Pattern Recognition