Efficient Laplace Approximation for Bayesian Registration Uncertainty Quantification
© Springer Nature Switzerland AG 2018. This paper presents a novel approach to modeling the posterior distribution in image registration that is computationally efficient for large deformation diffeomorphic metric mapping (LDDMM). We develop a Laplace approximation of Bayesian registration models en...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer International Publishing
2021
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| Online Access: | https://hdl.handle.net/1721.1/138063 |