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Efficient Laplace Approximation for Bayesian Registration Uncertainty Quantification

This paper presents a novel approach to modeling the pos terior distribution in image registration that is computationally efficient for large deformation diffeomorphic metric mapping (LDDMM). We develop a Laplace approximation of Bayesian registration models entirely in a bandlimited space that ful...

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Detalhes bibliográficos
Publicado no:Med Image Comput Comput Assist Interv
Main Authors: Wang, Jian, Wells, William M., Golland, Polina, Zhang, Miaomiao
Formato: Artigo
Idioma:Inglês
Publicado em: 2018
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6533616/
https://ncbi.nlm.nih.gov/pubmed/31134217
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/978-3-030-00928-1_99
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