通过动态注意力机制提升内窥镜息肉诊断的可解释性与准确性
Dynamic Contextual Attention Network: Transforming Spatial Representations into Adaptive Insights for Endoscopic Polyp Diagnosis
- 用自适应注意力机制动态聚焦关键息肉区域
- 无需显式定位模块即可提升诊断准确率
- 适合临床医生辅助决策与医学影像算法研究者
结直肠息肉是早期发现结直肠癌的关键指标。然而，传统内窥镜成像在息肉准确定位和全面上下文感知方面存在不足，影响诊断的可解释性。为此，我们提出动态上下文注意力网络（DCAN），该方法将空间表征转化为自适应的上下文洞察，利用注意力机制增强对关键息肉区域的关注，而无需显式定位模块。通过将上下文感知融入分类过程，DCAN提升了决策可解释性与整体诊断性能。这一成像技术的进步有望实现更可靠的结直肠癌检测，改善患者预后。
原文摘要 · Abstract (English)
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.
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