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Conference Papers Year : 2019

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

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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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Dates and versions

inserm-02099958 , version 1 (15-04-2019)
inserm-02099958 , version 2 (06-06-2019)

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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 - 16th IEEE International Symposium on Biomedical Imaging, Apr 2019, Venise, Italy. pp.1038-1041, ⟨10.1109/ISBI.2019.8759508⟩. ⟨inserm-02099958v2⟩
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