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
INSERM UMR1129, CEA/Neurospin/UNIACT,
Universit Paris Descartes, Sorbonne Paris Cit, Paris,
UMR992, CEA/Neurospin/UNICOG, Universit Paris Sud,
of Concepcin/Departamento de Ingeniera Elctrica,
UMR1129, Universit Paris Descartes, Sorbonne Paris
Cit, Paris, France,
Department, CHU Hpital Sud, Rennes, 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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