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
Understanding how the spatial structure of blood vessel networks relates to their function in health...
Persistence landscapes are functional summaries of persistence diagrams designed to enable analysis ...
As more and more neuroanatomical data are made available through efforts such as NeuroMorpho.Org and...
New representations of tree-structured data objects, using ideas from topological data analysis, ena...
Complex data objects arise in many areas of modern science including evolutionary biology, nueroscie...
Understanding the common topological characteristics of the human brain network across a population ...
The brain structural connectome is generated by a collection of white matter fiber bundles construct...
The brain structural connectome is generated by a collection of white matter fiber bundles construct...
This study introduces a new method of visualizing complex tree structured objects. The usefulness of...
Data analysis on non-Euclidean spaces, such as tree spaces, can be challenging. The main contributio...
Highly developed science and technology from the last two decades motivated the study of complex dat...
AbstractA method for the use of persistent homology in the statistical analysis of landmark-based sh...
Persistent homology (PH) is an algorithmic method that allows one to study shape and higher-order in...
<div><p>Data analysis on non-Euclidean spaces, such as tree spaces, can be challenging. The main con...
The active field of Functional Data Analysis (about understanding the variation in a set of curves) ...
Understanding how the spatial structure of blood vessel networks relates to their function in health...
Persistence landscapes are functional summaries of persistence diagrams designed to enable analysis ...
As more and more neuroanatomical data are made available through efforts such as NeuroMorpho.Org and...
New representations of tree-structured data objects, using ideas from topological data analysis, ena...
Complex data objects arise in many areas of modern science including evolutionary biology, nueroscie...
Understanding the common topological characteristics of the human brain network across a population ...
The brain structural connectome is generated by a collection of white matter fiber bundles construct...
The brain structural connectome is generated by a collection of white matter fiber bundles construct...
This study introduces a new method of visualizing complex tree structured objects. The usefulness of...
Data analysis on non-Euclidean spaces, such as tree spaces, can be challenging. The main contributio...
Highly developed science and technology from the last two decades motivated the study of complex dat...
AbstractA method for the use of persistent homology in the statistical analysis of landmark-based sh...
Persistent homology (PH) is an algorithmic method that allows one to study shape and higher-order in...
<div><p>Data analysis on non-Euclidean spaces, such as tree spaces, can be challenging. The main con...
The active field of Functional Data Analysis (about understanding the variation in a set of curves) ...
Understanding how the spatial structure of blood vessel networks relates to their function in health...
Persistence landscapes are functional summaries of persistence diagrams designed to enable analysis ...
As more and more neuroanatomical data are made available through efforts such as NeuroMorpho.Org and...