Persistent Homology Analysis of Brain Artery Trees.
Persistent Homology Analysis of Brain Artery Trees.
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DOI：
10.1214/15-aoas886
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
Skwerer S
中科院分区：
文献类型：
--
作者：
Bendich P;Marron JS;Miller E;Pieloch A;Skwerer S
使用拓扑数据分析中的思想，可以改善对脑动脉树群的统计分析的思想，对树木结构数据对象的新表示。每个数据树的许多表示形式来自持续图，这些图量化了多个尺度的血管的分支和循环。相对于此数据集的早期分析，通过持久图的各种摘要，通过持久图的各种摘要，与统计分析的新方法相关。即使控制了早期显着摘要的相关性，与年龄的相关性仍然显着。
New representations of tree-structured data objects, using ideas from topological data analysis, enable improved statistical analyses of a population of brain artery trees. A number of representations of each data tree arise from persistence diagrams that quantify branching and looping of vessels at multiple scales. Novel approaches to the statistical analysis, through various summaries of the persistence diagrams, lead to heightened correlations with covariates such as age and sex, relative to earlier analyses of this data set. The correlation with age continues to be significant even after controlling for correlations from earlier significant summaries.