@Article{LauraIgual2012,
author="Laura Igual
and Joan Carles Soliva
and Sergio Escalera
and Roger Gimeno
and Oscar Vilarroya
and Petia Radeva",
title="Automatic Brain Caudate Nuclei Segmentation and Classification in Diagnostic of Attention-Deficit/Hyperactivity Disorder",
journal="Computerized Medical Imaging and Graphics",
year="2012",
volume="36",
number="8",
pages="591--600",
optkeywords="Automatic caudate segmentation",
optkeywords="Attention-Deficit/Hyperactivity Disorder",
optkeywords="Diagnostic test",
optkeywords="Machine learning",
optkeywords="Decision stumps",
optkeywords="Dissociated dipoles",
abstract="We present a fully automatic diagnostic imaging test for Attention-Deficit/Hyperactivity Disorder diagnosis assistance based on previously found evidences of caudate nucleus volumetric abnormalities. The proposed method consists of different steps: a new automatic method for external and internal segmentation of caudate based on Machine Learning methodologies; the definition of a set of new volume relation features, 3D Dissociated Dipoles, used for caudate representation and classification. We separately validate the contributions using real data from a pediatric population and show precise internal caudate segmentation and discrimination power of the diagnostic test, showing significant performance improvements in comparison to other state-of-the-art methods.",
optnote="OR; HuPBA; MILAB",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=2143), last updated on Fri, 19 Sep 2014 10:26:55 +0200",
doi="10.1016/j.compmedimag.2012.08.002",
opturl="http://dx.doi.org/10.1016/j.compmedimag.2012.08.002",
file=":http://refbase.cvc.uab.es/files/ISE2012.pdf:PDF"
}