High-Risk Factor Prediction in Lung Cancer Using Thin-CT Scans: An Attention-Enhanced Graph Convolutional Network Approach
发布时间：2024-04-26浏览量：
该论文提出了一种融合注意力机制的图卷积神经网络（AE-GCN），旨在准确识别肺结节的高危因子。现有研究表明，具有微乳头状、实体型等病理高危特征的肺癌患者，在接受某些特定手术后复发风险较高。因此，在选择胸外科手术方案时，对这类高危肺结节的精确识别至关重要。本研究通过引入GCN模型来建模切片之间的空间特征，并利用注意力机制捕获切片级别的语义信息，从而实现对高危肺结节的术前准确诊断。
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