Name
Abstract | ||
|---|---|---|
The statistical analysis of functional magnetic resonance imaging (fMRI) is used to extract functional data of cerebral activation during a given experimental task. It allows for assessing changes in cerebral function related to cerebral activities. This methodology has been widely used and a few initiatives aim to develop shared data resources. Searching these data resources for a specific research goal remains a challenging problem. In particular, work is needed to create a global content-based (CB) fMRI retrieval capability.This work presents a CB fMRI retrieval approach based on the brain activation maps extracted using Probabilistic Independent Component Analysis (PICA). We obtained promising results on data from a variety of experiments which highlight the potential of the system as a tool that provides support for finding hidden similarities between brain activation maps. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-47103-7_17 | BRAIN INFORMATICS AND HEALTH |
Keywords | DocType | Volume |
fMRI retrieval, PICA, Brain activation map | Conference | 9919 |
ISSN | Citations | PageRank |
0302-9743 | 0 | 0.34 |
References | Authors | |
10 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alba García Seco de Herrera | 1 | 216 | 16.48 |
| L. Rodney Long | 2 | 534 | 56.98 |
| Sameer Antani | 3 | 1402 | 134.03 |