Back to articles
Volume: 28 | Article ID: art00006
Image
Intrinsic Geometry Visualization for the Interactive Analysis of Brain Connectivity Patterns
  DOI :  10.2352/ISSN.2470-1173.2016.1.VDA-481  Published OnlineFebruary 2016
Abstract

Understanding how brain regions are interconnected is an important topic within the domain of neuroimaging. Advances in non-invasive technologies enable larger and more detailed images to be collected more quickly than ever before. These data contribute to create what is usually referred to as a connectome, that is, a comprehensive map of neural connections. The availability of connectome data allows for more interesting questions to be asked and more complex analyses to be conducted. In this paper we present a novel web-based 3D visual analytics tool that allows user to interactively explore the intrinsic geometry of the connectome. That is, brain data that has been transformed through a dimensionality reduction step, such as multidimensional scaling (MDS), Isomap, or t-distributed stochastic neighbor embedding (t-SNE) techniques. We evaluate our tool through a series of real-world case studies, demonstrating its effectiveness in aiding domain experts for a range of neuroimaging tasks.

Subject Areas :
Views 13
Downloads 3
 articleview.views 13
 articleview.downloads 3
  Cite this article 

Giorgio Conte, Allen Ye, Kyle Almryde, Olusola Ajilore, Alex Leow, Angus Graeme Forbes, "Intrinsic Geometry Visualization for the Interactive Analysis of Brain Connectivity Patternsin Proc. IS&T Int’l. Symp. on Electronic Imaging: Visualization and Data Analysis,  2016,  https://doi.org/10.2352/ISSN.2470-1173.2016.1.VDA-481

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2016
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology