We present a method that provides relevant distances or similarity measures between temporal series of brain functional images. The method allows to perform a multivariate comparison between data sets of several subjects in the time or in the space domain. These analyses are important to assess globally the inter subject variability before averaging subjects to draw some conclusions at the population level. We adapt the RV-coefficient to measure meaningful spatial or temporal similarities and use multidimensional scaling for visualisation.
CITATION STYLE
Kherif, F., Flandin, G., Ciuciu, P., Benali, H., Simon, O., & Poline, J. B. (2002). Model based spatial and temporal similarity measures between series of functional magnetic resonance images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2489, pp. 509–516). Springer Verlag. https://doi.org/10.1007/3-540-45787-9_64
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