Diffusion-based spatial priors for imaging

  title={Diffusion-based spatial priors for imaging},
  author={Lee M. Harrison and William D. Penny and John Ashburner and Nelson J. Trujillo-Barreto and Karl J. Friston},
We describe a Bayesian scheme to analyze images, which uses spatial priors encoded by a diffusion kernel, based on a weighted graph Laplacian. This provides a general framework to formulate a spatial model, whose parameters can be optimized. The application we have in mind is a spatiotemporal model for imaging data. We illustrate the method on a random effects analysis of fMRI contrast images from multiple subjects; this simplifies exposition of the model and enables a clear description of its… CONTINUE READING


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