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Feature-similarity visualization of MRI cortical surface data

机译:MRI皮质表面数据的特征相似性可视化

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We present an analytics-based framework for simultaneous visualization of large surface data collections arising in clinical neuroimaging studies. Termed Informatics Visualization for Neuroimaging (INVIZIAN), this framework allows the visualization of both cortical surfaces characteristics and feature relatedness in unison. It also uses dimension reduction methods to derive new coordinate systems using a Jensen-Shannon divergence metric for positioning cortical surfaces in a metric space such that the proximity in location is proportional to neuroanatomical similarity. Feature data such as thickness and volume are colored on the cortical surfaces and used to display both subject-specific feature values and global trends within the population. Additionally, a query-based framework allows the neuroscience researcher to investigate probable correlations between neuroanatomical and subject patient attribute values such as age and diagnosis.
机译:我们提出了一种基于分析的课程,用于同时可视化临床神经影像研究中产生的大型表面数据收集。被称为神经影像动物的信息性可视化(Invizian),该框架允许在齐声统一中可视化皮质表面特性和功能相关性。它还使用尺寸减少方法来使用Jensen-Shannon发散度量来导出新的坐标系,用于定位在度量空间中的皮质表面,使得位置的邻近与神经杀菌相似性成比例。诸如厚度和体积之类的功能数据在皮质表面上是着色的,并用于显示人口中的主题特定特征值和全局趋势。此外,基于查询的框架允许神经科学研究员调查神经杀菌和主语患者属性值(如年龄和诊断)之间的可能相关性。

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