Unbiased longitudinal brain atlas creation using robust linear registration and log-Euclidean framework for diffeomorphisms

Antoine Legouhy 1 Olivier Commowick 1 François Rousseau 2 Christian Barillot 1
1 Empenn
INSERM - Institut National de la Santé et de la Recherche Médicale, Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
Abstract : We present a new method to create a diffeomorphic longitudinal (4D) atlas composed of a set of 3D atlases each representing an average model at a given age. This is achieved by generalizing atlasing methods to produce atlases unbiased with respect to the initial reference up to a rigid transformation and ensuring diffeomorphic deformations thanks to the Baker-Campbell-Hausdorff formula and the log-Euclidean framework for diffeomorphisms. Subjects are additionally weighted using an asymmetric function to closely match specified target ages. Creating a longitudinal atlas also implies dealing with subjects with large brain differences that can lead to registration errors. This is overcome by a robust rigid registration based on polar decomposition. We illustrate these techniques for the creation of a 4D pediatric atlas, showing their ability to create a temporally consistent atlas.
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https://www.hal.inserm.fr/inserm-02099958
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Submitted on : Thursday, June 6, 2019 - 3:39:33 PM
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  • HAL Id : inserm-02099958, version 2

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Antoine Legouhy, Olivier Commowick, François Rousseau, Christian Barillot. Unbiased longitudinal brain atlas creation using robust linear registration and log-Euclidean framework for diffeomorphisms. ISBI 2019 - IEEE International Symposium on Biomedical Imaging, Apr 2019, Venise, Italy. pp.1038-1041. ⟨inserm-02099958v2⟩

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