Partial sparse canonical correlation analysis (PSCCA) for population studies in medical imaging

@article{Dhillon2012PartialSC,
  title={Partial sparse canonical correlation analysis (PSCCA) for population studies in medical imaging},
  author={Paramveer S. Dhillon and Brian B. Avants and Lyle H. Ungar and James C. Gee},
  journal={2012 9th IEEE International Symposium on Biomedical Imaging (ISBI)},
  year={2012},
  pages={1132-1135}
}
We propose a new multivariate method, partial sparse canonical correlation analysis (PSCCA), for computing the statistical comparisons needed by population studies in medical imaging. PSCCA is a multivariate generalization of linear regression that allows one to statistically parameterize imaging studies in terms of multiple views of the population (e.g., the full collection of measurements taken from an image set along with batteries of cognitive or genetic data) while controlling for nuisance… CONTINUE READING

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