Title:FAIR Rigidity and Constraint Image Registration

Image registration is one of the most challenging tasks within digital imaging. Given two images R and T, one is looking for a transformation y such that a deformed version T(y(x)) of T is similar to R. The problem arises, for example, when images taken from different objects, perspectives, times, or devices need to be compared or fused. Image registration, and in particular medical image registration, has been subject to extensive studies in the past years. Its versatile and important applications have attracted researchers from various branches. In this talk, we present new approaches to constrained image registration and in particular to local rigidity constraints. We demonstrate how to formalize and incorporate local rigidity as a constraint on the transformation in a very general variational framework. Soft (penalty) and hard constrained approaches are developed, discussed and compared.