A robust statistics-based global energy function for the alignment of serially acquired autoradiographic sections

dc.contributor.authorNikou, C.en
dc.contributor.authorHeitz, F.en
dc.contributor.authorNehlig, A.en
dc.contributor.authorNamer, I. J.en
dc.contributor.authorArmspach, J. P.en
dc.date.accessioned2015-11-24T17:00:26Z
dc.date.available2015-11-24T17:00:26Z
dc.identifier.issn0165-0270-
dc.identifier.urihttps://olympias.lib.uoi.gr/jspui/handle/123456789/10768
dc.rightsDefault Licence-
dc.subjectserially acquired imagesen
dc.subjectalignmenten
dc.subjectimage registrationen
dc.subjectpixel similarity measureen
dc.subjectrobust estimationen
dc.subjectthree dimensional reconstructionen
dc.subjectautoradiographyen
dc.subject3-dimensional reconstructionen
dc.subjectimagesen
dc.subjectregistrationen
dc.subjectinformationen
dc.titleA robust statistics-based global energy function for the alignment of serially acquired autoradiographic sectionsen
heal.abstractAutoradiographic analysis of the functional changes occurring in the rat brain are most often performed on coronal sections that allow a good insight into the events occurring at the structural level but lacks the 3D context which is necessary to fully understand the involvement of the brain structures in specific situations like focal seizures with or without generalization. Therefore a robust, fully-automated algorithm for the registration of serially acquired autoradiographic sections is presented. The method accounts for the main difficulties of autoradiographic alignment: corrupted data (cuts and tears), dissimilarities or discontinuities between slices, non parallel or missing slices. The approach relies on the minimization of a global energy function based on robust statistics. The energy function measures the similarity between a slice and its neighborhood in the 3D volume. No particular direction is privileged in the method, so that global offsets, biases in the estimation or error propagations are avoided. The method is evaluated qualitatively and quantitatively on real autoradiographic data. Rat brain autoradiographic volumes are reconstructed with registration errors less than 1 degree in rotation and less than 1 pixel in translation. (C) 2003 Elsevier Science B.V. All rights reserved.en
heal.accesscampus-
heal.fullTextAvailabilityTRUE-
heal.identifier.primaryDoi 10.1016/S0165-0270(02)00369-2-
heal.journalNameJ Neurosci Methodsen
heal.journalTypepeer reviewed-
heal.languageen-
heal.publicationDate2003-
heal.recordProviderΠανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Μηχανικών Ηλεκτρονικών Υπολογιστών και Πληροφορικήςel
heal.typejournalArticle-
heal.type.elΆρθρο Περιοδικούel
heal.type.enJournal articleen

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