Diffeomorphic registration with sliding conditions : Application to the registration of lungs CT images

In this paper, we propose a novel diffeomorphic registration method for respiratory motion correction, taking the sliding motion of organs into account. Modelling sliding conditions in image registration has recently gained a strong interest in the medical imaging community. It allows to estimate physiologically realistic deformations at the boundaries of organs like the lungs. This potentially leads to a more accurate registration within the organs. An issue with these algorithms is that they either estimate organ motion within regions of interest only, or they do not ensure the invertibility of the deformations. We propose a strategy to incorporate sliding motion modelling into a piecewise diffeomorphic image registration algorithm inspired by the LogDemons algorithm. Encoding the deformations in velocity fields instead of standard displacement fields ensures the invertibility of the deformations, even at the boundaries where the sliding motion is modelled. We show that our methodology is computationally tractable for serial 3D CT images of the lungs and that it estimates more plausible deformations than by using LDDMM diffeomorphic registration without sliding conditions.

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