title: A univocal definition of the neuronal soma morphology using Gaussian mixture models.
abstract: The definition of the soma is fuzzy, as there is no clear line demarcating the soma of the labeled neurons and the origin of the dendrites and axon. Thus, the morphometric analysis of the neuronal soma is highly subjective. In this paper, we provide a mathematical definition and an automatic segmentation method to delimit the neuronal soma. We applied this method to the characterization of pyramidal cells, which are the most abundant neurons in the cerebral cortex. Since there are no benchmarks with which to compare the proposed procedure, we validated the goodness of this automatic segmentation method against manual segmentation by neuroanatomists to set up a framework for comparison. We concluded that there were no significant differences between automatically and manually segmented somata, i.e., the proposed procedure segments the neurons similarly to how a neuroanatomist does. It also provides univocal, justifiable and objective cutoffs. Thus, this study is a means of characterizing pyramidal neurons in order to objectively compare the morphometry of the somata of these neurons in different cortical areas and species.
authors.affiliation: Computational Intelligence Group, Departamento de Inteligencia Artificial, Escuela Técnica Superior de Ingenieros Informáticos, Universidad Politécnica de Madrid, Campus Montegancedo Madrid, Spain.
authors.forename: Sergio
authors.initials: S
authors.lastname: Luengo-Sanchez
authors.affiliation: Computational Intelligence Group, Departamento de Inteligencia Artificial, Escuela Técnica Superior de Ingenieros Informáticos, Universidad Politécnica de Madrid, Campus Montegancedo Madrid, Spain.
authors.forename: Concha
authors.initials: C
authors.lastname: Bielza
authors.affiliation: Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Campus Montegancedo Madrid, Spain ; Consejo Superior de Investigaciones Científicas, Instituto Cajal Madrid, Spain ; Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III Madrid, Spain.
authors.forename: Ruth
authors.initials: R
authors.lastname: Benavides-Piccione
authors.affiliation: Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Campus Montegancedo Madrid, Spain ; Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III Madrid, Spain.
authors.forename: Isabel
authors.initials: I
authors.lastname: Fernaud-Espinosa
authors.affiliation: Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Campus Montegancedo Madrid, Spain ; Consejo Superior de Investigaciones Científicas, Instituto Cajal Madrid, Spain ; Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas, Instituto de Salud Carlos III Madrid, Spain.
authors.forename: Javier
authors.initials: J
authors.lastname: DeFelipe
authors.affiliation: Computational Intelligence Group, Departamento de Inteligencia Artificial, Escuela Técnica Superior de Ingenieros Informáticos, Universidad Politécnica de Madrid, Campus Montegancedo Madrid, Spain.
authors.forename: Pedro
authors.initials: P
authors.lastname: Larrañaga
keywords: Gaussian mixture model; mesh comparison; morphology validation; repair and segmentation; three-dimensional soma reconstruction