Jesper Leif Roger Andersson1, Mark Jenkinson1
1fMRIB, Oxford University, Oxford, Oxfordshire, United Kingdom
We have developed a method for estimating and correcting distortions from reverse-blip data with poor SNR. It is based on a forward model that allows us to make predictions about the images and a Rician noise model that enables us to calculate the probability of observed images. Bayesian inversion is used to find the most probable distortion-free image and field. It performs well even on data with very poor SNR.