%0 Journal Article
%T A fully-automatic caudate nucleus segmentation of brain MRI: Application in volumetric analysis of pediatric attention-deficit/hyperactivity disorder
%A Laura Igual
%A Joan Soliva
%A Antonio Hern¨˘ndez-Vela
%A Sergio Escalera
%A Xavier Jim¨Śnez
%A Oscar Vilarroya
%A Petia Radeva
%J BioMedical Engineering OnLine
%D 2011
%I BioMed Central
%R 10.1186/1475-925x-10-105
%X We present Cau-dateCut: a new fully-automatic method of segmenting the caudate nucleus in MRI. CaudateCut combines an atlas-based segmentation strategy with the Graph Cut energy-minimization framework. We adapt the Graph Cut model to make it suitable for segmenting small, low-contrast structures, such as the caudate nucleus, by defining new energy function data and boundary potentials. In particular, we exploit information concerning the intensity and geometry, and we add supervised energies based on contextual brain structures. Furthermore, we reinforce boundary detection using a new multi-scale edgeness measure.We apply the novel CaudateCut method to the segmentation of the caudate nucleus to a new set of 39 pediatric attention-deficit/hyperactivity disorder (ADHD) patients and 40 control children, as well as to a public database of 18 subjects. We evaluate the quality of the segmentation using several volumetric and voxel by voxel measures. Our results show improved performance in terms of segmentation compared to state-of-the-art approaches, obtaining a mean overlap of 80.75%. Moreover, we present a quantitative volumetric analysis of caudate abnormalities in pediatric ADHD, the results of which show strong correlation with expert manual analysis.CaudateCut generates segmentation results that are comparable to gold-standard segmentations and which are reliable in the analysis of differentiating neuroanatomical abnormalities between healthy controls and pediatric ADHD.Studies of volumetric brain magnetic resonance imaging (MRI) show neuroanatomical abnormalities in pediatric attention-deficit/hyperactivity disorder (ADHD) [1-3]. ADHD is a developmental disorder characterized by inatten-tiveness, motor hyperactivity and impulsiveness, and it represents the most prevalent childhood psychiatric disorder. It is also estimated that half the children with ADHD will display the disorder in adulthood. As stated in several reviews and metanalyses, diminished right caudate
%K Brain caudate nucleus
%K segmentation
%K MRI
%K atlas-based strategy
%K Graph Cut framework
%U http://www.biomedical-engineering-online.com/content/10/1/105