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CCIMI Seminars

Diffusion bridge simulation in geometric statistics

With Frank van der Meulen, Delft University of Technology

Diffusion bridge simulation in geometric statistics

Geometric statistics has put forward various models for image deformation. Large deformation diffeomorphic metric mapping provides a framework for deforming a template image to a target image. The transformations are traditionally based on flows defined in terms of Ordinary Differential Equations (ODEs). More recently, stochastic models have been proposed where the ODE is replaced by a stochastic differential equation. Finding a common template image turns out to be closely connected to diffusion bridge simulation in high dimension. For the related but somewhat simpler case 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 papers.

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