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@INCOLLECTION{GLA2016,
     author = {Garc{\'{\i}}a Seco de Herrera, Alba and Long, L. Rodney and Antani, Sameer},
   keywords = {brain activation map, fMRI retrieval, PICA},
      title = {Content–based fMRI Brain Maps Retrieval},
  booktitle = {International Conference on Brain Informatics & Health (BIH)},
       year = {2016},
  publisher = {Springer LNCS/LNAI},
   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.}
}