Hierarchical Image Registration with an Active Contour-Based Atlas Registration Model
This paper proposes to apply the non parametric atlas registration framework we have recently developed in . This technique derived from the optical flow model and the active contour framework allows to base the registration of an anatomical atlas on selected structures. A well-suited application of our model is the non rigid registration of medical images based on a hierarchical atlas. This hierarchical registration approach that we have previously introduced in , aims to better exploit the spatial dependencies that exist between anatomical structures in an image matching process. Its basic idea is to first register the structures the most relevant to estimate the deformation in order to help the registration of secondary structures. This aims to reduce the risks of mismatching. Here, we propose to test our novel simultaneous registration and segmentation model on different types of medical image registration problems. Results show the advantages to combine our active contour-based registration framework with the structure-based hierarchical approach and highlight the importance of the registration order of the anatomical structures.