首页> 外文会议>International conference on medical imaging computing and computer-assisted intervention >Revealing Regional Associations of Cortical Folding Alterations with In Utero Ventricular Dilation Using Joint Spectral Embedding
【24h】

Revealing Regional Associations of Cortical Folding Alterations with In Utero Ventricular Dilation Using Joint Spectral Embedding

机译:使用联合频谱嵌入揭示具有子宫室扩张的皮质折叠改变的区域关联

获取原文

摘要

Fetal ventriculomegaly (VM) is a condition with dilation of one or both lateral ventricles, and is diagnosed as an atrial diameter larger than 10 mm. Evidence of altered cortical folding associated with VM has been shown in the literature. However, existing studies use a holistic approach (i.e., ventricle as a whole) based on diagnosis or ventricular volume, thus failing to reveal the spatially-heterogeneous association patterns between cortex and ventricle. To address this issue, we develop a novel method to identify spatially fine-scaled association maps between cortical development and VM by leveraging vertex-wise correlations between the growth patterns of both ventricular and cortical surfaces in terms of area expansion and curvature information. Our approach comprises multiple steps. In the first step, we define a joint graph Laplacian matrix using cortex-to-ventricle correlations. Next, we propose a spectral embedding of the cortex-to-ventricle graph into a common underlying space where their joint growth patterns are projected. More importantly, in the joint ventricle-cortex space, the vertices of associated regions from both cortical and ventricular surfaces would lie close to each other. In the final step, we perform clustering in the joint embedded space to identify associated sub-regions between cortex and ventricle. Using a dataset of 25 healthy fetuses and 23 fetuses with isolated non-severe VM within the age range of 26-29 gestational weeks, our results show that the proposed approach is able to reveal clinically relevant and meaningful regional associations.
机译:胎儿脑室肥大(VM)是一侧或两侧侧脑室扩张的情况,被诊断为房径大于10毫米。与VM相关的皮质折叠改变的证据已在文献中显示。然而,现有的研究基于诊断或心室容积使用整体方法(即,整个心室),因此未能揭示皮质与心室之间的空间异质性关联模式。为了解决这个问题,我们开发了一种新颖的方法,可以通过利用心室和皮质表面的生长模式之间的面积相关性和曲率信息在顶点方向上的相关性来识别皮质发育和VM之间的空间精细缩放的关联图。我们的方法包括多个步骤。第一步,我们使用皮质与心室的相关性定义联合图拉普拉斯矩阵。接下来,我们建议将皮层到心室图的频谱嵌入到一个共同的基础空间中,在这些空间中可以预测它们的联合生长模式。更重要的是,在联合心室-皮质空间中,来自皮质和心室表面的相关区域的顶点将彼此靠近。在最后一步,我们在联合嵌入空间中进行聚类,以识别皮质和心室之间的相关子区域。使用25个健康胎儿和23个胎儿的数据集,这些胎儿在26-29个孕周的年龄范围内分离出非严重性VM,我们的结果表明,提出的方法能够揭示临床上相关且有意义的区域关联。

著录项

相似文献

  • 外文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号