MRI Iterative Super Resolution with Wiener Filter Regularization

The swallowing process affects several aspects of one's welfare, as nutrition, hydration, respiration and hearing. Magnetic resonance imaging (MRI) has been a valuable tool to study swallowing, since it is a non-invasive procedure that can dynamically capture the shapes of the tongue and other elements involved in the process. The resolution enhancement of the MRI frames support directly diseases diagnoses, helping the visual analysis, or can be a pre-processing tool to segmentation, classification, recognition or modelling. MRI frames with better resolution, with less blurring or noise can be obtained changing the acquisition process, or using more powerful devices, but the cost of this solution is higher than applying computational Super-Resolution (SR) techniques. This paper studies a Bayesian approach to provide a Wiener filter to regularize the conjugate gradient solution, and promote an adaptation of an iterative SR method for non-rigid registration that can be generalized to other iterative SR methods.