首页> 外文会议>IEEE Conference on Visual Analytics Science amp; Technology 2012. >Feature-similarity visualization of MRI cortical surface data
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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:我们提出了一个基于分析的框架,用于同时可视化临床神经影像研究中产生的大量表面数据。称为神经影像学的信息学可视化(INVIZIAN),该框架允许一致地可视化皮层表面特征和特征相关性。它还使用降维方法使用Jensen-Shannon发散度量标准来导出新的坐标系,以将皮质表面放置在度量标准空间中,以使位置的接近度与神经解剖学相似度成比例。诸如厚度和体积之类的特征数据在皮质表面上被着色,并用于显示特定于受试者的特征值和总体中的总体趋势。此外,基于查询的框架允许神经科学研究者研究神经解剖学和受试者患者属性值(例如年龄和诊断)之间的可能相关性。

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