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SUMMARY:Diffusion bridge simulation in geometric statistics - Frank van de
 r Meulen\, Delft University of Technology
DTSTART:20190522T130000Z
DTEND:20190522T140000Z
UID:TALK115483@talks.cam.ac.uk
CONTACT:Alberto J Coca
DESCRIPTION:Geometric statistics has put forward various models for image 
 deformation. _Large deformation diffeomorphic metric mapping_ provides a f
 ramework for deforming a template image to a target image. The transformat
 ions are traditionally based on flows defined in terms of Ordinary Differe
 ntial Equations (ODEs). More recently\, stochastic models have been propos
 ed where the ODE is replaced by a stochastic differential equation. Findin
 g a common template image turns out to be closely connected to diffusion b
 ridge simulation in high dimension. For the related but somewhat simpler c
 ase of landmark registration\, I will discuss how this can be accomplished
  using _guided diffusion processes_\, as originally defined in Schauer et 
 al. (Bernoulli 23(4)\, 2917-2950) and further developed in follow-up paper
 s. 
LOCATION:CMS\, MR14
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