Quantifying Registration Uncertainty With Sparse Bayesian Modelling

IEEE Transactions on Medical Imaging, pp. 607-617, 2017.

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UncertaintyBayes methodsData modelsMarkov processesAdaptation modelsMore(2+)

Abstract:

We investigate uncertainty quantification under a sparse Bayesian model of medical image registration. Bayesian modelling has proven powerful to automate the tuning of registration hyperparameters, such as the trade-off between the data and regularization functionals. Sparsity-inducing priors have recently been used to render the parametr...More

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