Finding imaging patterns of structural covariance via Non-Negative Matrix Factorization

@article{Sotiras2015FindingIP,
  title={Finding imaging patterns of structural covariance via Non-Negative Matrix Factorization},
  author={Aristeidis Sotiras and Susan M. Resnick and Christos Davatzikos},
  journal={NeuroImage},
  year={2015},
  volume={108},
  pages={1-16}
}
In this paper, we investigate the use of Non-Negative Matrix Factorization (NNMF) for the analysis of structural neuroimaging data. The goal is to identify the brain regions that co-vary across individuals in a consistent way, hence potentially being part of underlying brain networks or otherwise influenced by underlying common mechanisms such as genetics and pathologies. NNMF offers a directly data-driven way of extracting relatively localized co-varying structural regions, thereby… CONTINUE READING
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