Abstract
In this paper, we present a new multimodal image registration technique established on elastodynamics notion. The main idea behind this concept is the progression of waves on an elastic body as soon as it is disturbed from its initial rest state. We propose to solve the multimodal registration problem by modeling the non-linear deformations as elastic waves and iteratively solving the elastodynamics wave equation to estimate the transformation. The inertial force in elastodynamics model is computed as the gradient of mutual information which considers the statistical relationship between the intensities of the images acquired using different imaging modalities. We tested our method on T1–T2 weighted MR brain image pairs and MR-CT brain image pairs. The proposed registration technique was compared against a variant of demons method proposed for multimodal images. The registration results were analyzed by examining the overlay images and by computing the normalized mutual information. The qualitative and quantitative analysis proved that our proposed method registers the images better than the compared method.
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Available at: http://brainweb.bic.mni.mcgill.ca/brainweb/.
Available at: http://www.insight-journal.org/rire/.
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Ahmad, S., Khan, M.F. Multimodal non-rigid image registration based on elastodynamics. Vis Comput 34, 21–27 (2018). https://doi.org/10.1007/s00371-016-1307-z
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DOI: https://doi.org/10.1007/s00371-016-1307-z