%0 Conference Proceedings
%T Automatic Internal Segmentation of Caudate Nucleus for Diagnosis of Attention Deficit Hyperactivity Disorder
%A Laura Igual
%A Joan Carles Soliva
%A Roger Gimeno
%A Sergio Escalera
%A Oscar Vilarroya
%A Petia Radeva
%B 9th International Conference on Image Analysis and Recognition
%D 2012
%V 7325
%N II
%@ 0302-9743
%@ 978-3-642-31297-7
%F Laura Igual2012
%O OR; HuPBA; MILAB
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=2059), last updated on Fri, 19 Sep 2014 10:23:57 +0200
%X PosterStudies on volumetric brain Magnetic Resonance Imaging (MRI) showed neuroanatomical abnormalities in pediatric Attention-Deficit/Hyperactivity Disorder (ADHD). In particular, the diminished right caudate volume is one of the most replicated findings among ADHD samples in morphometric MRI studies. In this paper, we propose a fully-automatic method for internal caudate nucleus segmentation based on machine learning. Moreover, the ratio between right caudate body volume and the bilateral caudate body volume is applied in a ADHD diagnostic test. We separately validate the automatic internal segmentation of caudate in head and body structures and the diagnostic test using real data from ADHD and control subjects. As a result, we show accurate internal caudate segmentation and similar performance among the proposed automatic diagnostic test and the manual annotation.
%U http://refbase.cvc.uab.es/files/ISG2012.pdf
%U http://dx.doi.org/10.1007/978-3-642-31298-4_27
%P 222-229