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Abstract #2856

Creating a child brain connectivity atlas for reliable bundle identification in developmental studies

Sofya Kulikova 1 , Jessica Dubois 2 , Pamela Guevara 3 , Jean-Franois Mangin 4 , Catherine Chiron 5 , Nicole Chemaly 5 , Silvia Napuri 6 , Cyril Poupon 7 , and Lucie Hertz-Pannier 1

1 INSERM UMR1129, CEA/Neurospin/UNIACT, Universit Paris Descartes, Sorbonne Paris Cit, Paris, France, 2 INSERM UMR992, CEA/Neurospin/UNICOG, Universit Paris Sud, Paris, France, 3 University of Concepcin/Departamento de Ingeniera Elctrica, Chile, 4 CEA/Neurospin/UNATI, Gif-sur-Yvette, France, 5 INSERM UMR1129, Universit Paris Descartes, Sorbonne Paris Cit, Paris, France, 6 Pediatric Department, CHU Hpital Sud, Rennes, France, 7 CEA/Neurospin/UNIRS, Gif-sur-Yvette, France

Tractography datasets are extremely complex and extracting individual bundles from them is still a challenging task. Recently, fiber-clustering techniques that take into account fiber shapes and localization variabilities were proposed for automatic bundles identification, based on an atlas of main bundles. However, this atlas was generated for adults hindering its application to children as fiber shapes and lengths change during development. In this work we present a child brain connectivity atlas, which can be used in studies on normal and pathological brain development for automatic bundles identification and further evaluation of the MRI parameters across the identified bundles.

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