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Visualizing the structure of large trees. (English) Zbl 1274.62049

Summary: This study introduces a new method of visualizing complex tree structured objects. The usefulness of this method is illustrated in the context of detecting unexpected features in a data set of very large trees. The major contribution is a novel two-dimensional graphical representation of each tree, with a covariate coded by color.
The motivating data set contains three-dimensional representations of brain artery systems of 105 subjects. Due to inaccuracies inherent in the medical imaging techniques, issues with the reconstruction algorithms and inconsistencies introduced by manual adjustment, various discrepancies are present in the data. The proposed representation enables quick visual detection of the most common discrepancies. For our driving example, this tool led to the modification of 10% of the artery trees and deletion of 6.7%. The benefits of our cleaning method are demonstrated through a statistical hypothesis test on the effects of aging on vessel structure. The data cleaning resulted in improved significance levels. Our second example analyses brain artery images of healthy patients and patients with brain tumor. Our visualization can identify tumor patients.

MSC:

62A09 Graphical methods in statistics
62-07 Data analysis (statistics) (MSC2010)
62P10 Applications of statistics to biology and medical sciences; meta analysis
92C55 Biomedical imaging and signal processing

Software:

Dendroscope; iTOL
PDFBibTeX XMLCite
Full Text: DOI arXiv Euclid

References:

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