Indiana University-Purdue University Indianapolis (IUPUI) / A Multigraph is a set of graphs with a common set of nodes but different sets of
edges. Multigraph visualization has not received much attention so far. In this thesis, I
will introduce an interactive application in brain network data analysis that has a strong
need for multigraph visualization. For this application, multigraph was used to represent
brain connectome networks of multiple human subjects. A volumetric data set was
constructed from the matrix representation of the multigraph. A volume visualization
tool was then developed to assist the user to interactively and iteratively detect
network features that may contribute to certain neurological conditions. I applied this
technique to a brain connectome dataset for feature detection in the classification of
Alzheimer's Disease (AD) patients. Preliminary results showed significant improvements
when interactively selected features are used.
| Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/11828 |
| Date | 12 1900 |
| Creators | Wang, Jiachen |
| Contributors | Fang, Shiaofen |
| Source Sets | Indiana University-Purdue University Indianapolis |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
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