The paper presents a novel non parametric image registration method based on an explicit representation of the warping function. The image registration problem is approached in the Bayesian framework with a prior term given by a Gaussian random field accounting the regularity of a deformable grid. The algorithm is completely unsupervised, making it suitable for high throughput biomedical applications such as proteomics and cellular imaging.

A deformable grid approach for Bayesian image registration

Ceccarelli M;
2008

Abstract

The paper presents a novel non parametric image registration method based on an explicit representation of the warping function. The image registration problem is approached in the Bayesian framework with a prior term given by a Gaussian random field accounting the regularity of a deformable grid. The algorithm is completely unsupervised, making it suitable for high throughput biomedical applications such as proteomics and cellular imaging.
978-088986717-8
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12070/11598
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