Chamberland, Maxime ![]() ![]() ![]() ![]() |
Preview |
PDF
- Accepted Post-Print Version
Download (887kB) | Preview |
Abstract
Structural networks contain high dimensional data that raise huge computational and visualization problems, especially when attempting to characterise them using graph theory. As a result, it can be non-intuitive to grasp the contribution of each edge within a graph, both at a local and global scale. Here, we introduce a new platform that enables tractography-based networks to be explored in a highly interactive real-time fashion. The framework allows one to interactively tune graph-related parameters on the fly, as opposed to conventional visualization softwares that rely on pre-computed connectivity matrices. From a neurosurgical perspective, the method also provides enhanced understanding regarding the potential removal of a specific node or transection of an edge from the network, allowing surgeons and clinicians to discern the value of each node.
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Date Type: | Publication |
Status: | Published |
Schools: | Psychology Medicine |
Publisher: | Springer Verlag |
ISBN: | 978-3-319-67159-8 |
ISSN: | 0302-9743 |
Date of First Compliant Deposit: | 5 October 2017 |
Last Modified: | 14 Sep 2024 01:28 |
URI: | https://orca.cardiff.ac.uk/id/eprint/105132 |
Actions (repository staff only)
![]() |
Edit Item |