计算机科学 ›› 2022, Vol. 49 ›› Issue (3): 129-133.doi: 10.11896/jsjkx.201100152
周海榆, 张道强
ZHOU Hai-yu, ZHANG Dao-qiang
摘要： 近年来,图神经网络在神经性脑疾病诊断中的应用引起了广泛关注。然而,现有研究中使用的图通常只是基于简单的点对点连接,无法反映3个或更多受试者之间的复杂关联,尤其是在多中心数据集中,即由不同医疗机构所使用的不同采集设备和不同受试人群而集成的具有异质性的数据集。为解决医疗影像数据中存在的多中心异质性问题,提出了一种多中心超图数据结构来描述多中心数据之间的关系。这种超图由两种不同的超边构成,一种是描述单个中心内部关系的中心内超边,另一种是描述不同中心之间关系的跨中心超边。另外,还提出了一种超图卷积神经网络来学习节点的特征表示,这种超图卷积由两部分构成,第一部分是超图节点卷积,第二部分是超边卷积。在两个多中心数据集上的实验结果证明了所提方法的有效性。
中图分类号:
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