We present a generalisation of the brain segmentation algorithm implemented in the SPM software, which exploits variational Bayesian inference
We test the accuracy and robustness of our method in segmenting brain tissues using synthetic and real MRI data
We introduce an empirical Bayes framework to learn tissue specific intensity priors from large data sets