A hierarchical parametric algorithm for deformable multimodal image registration
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Updated: Aug 23, 2026

Multimodal Cross-Device and Marker-Free Co-Registration of Preclinical Imaging Modalities
Published on: October 27, 2023
Pierre Hellier1, Christian Barillot
1IRISA, INRIA-CNRS, Campus de Beaulieu, 35042 Rennes Cedex, France. phellier@irisa.fr
Abstract:
Image fusion is of utmost importance for many applications in image analysis. Particularly in medical imaging, images of different modalities are necessary because they provide complementary information that must be merged for an optimal use. The fusion of these images, which can be achieved through a registration process, makes it possible to superimpose all available information on the same frame. In many cases, a rigid transformation is sufficient to align correctly the images. However, there are cases where a non-rigid transformation is needed: geometrical distortions present in one image, non-rigid motion, etc. The purpose of this paper is to propose a generic method to account for these deformations in case of multimodal images. We have applied the algorithm in the particular context of 3D medical images and present results on simulated and real data.
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