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Multimodal Brain Warping Using the Demons Algorithm and Adaptative Intensity Corrections

Abstract : This paper presents an original method for three-dimensional elastic registration of multimodal images. We propose to make use of a scheme that iterates between correcting for intensity differences between images and performing standard monomodal registration. The core of our contribution resides in providing a method that finds the transformation that maps the intensities of one image to those of another. It makes the assumption that there are at most two functional dependencies between the intensities of structures present in the images to register, and relies on robust estimation techniques to evaluate these functions. We provide results showing successful registration between several imaging modalities involving segmentations, T1 magnetic resonance (MR), T2 MR, proton density (PD) MR and computed tomography (CT). We also argue that our intensity modeling may be more appropriate than mutual information (MI) in the context of evaluating high-dimensional deformations, as it puts more constraints on the parameters to be estimated and, thus, permits a better search of the parameter space.
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Submitted on : Wednesday, August 17, 2011 - 11:16:13 PM
Last modification on : Friday, February 4, 2022 - 3:22:20 AM
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  • HAL Id : inria-00615028, version 1



Alexandre Guimond, Alexis Roche, Nicholas Ayache, Jean Meunier. Multimodal Brain Warping Using the Demons Algorithm and Adaptative Intensity Corrections. IEEE Transactions on Medical Imaging, Institute of Electrical and Electronics Engineers, 2001, 20 (1), pp.58--69. ⟨inria-00615028⟩



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