3D segmentations of neuronal nuclei from confocal microscope image stacks

La Torre, Antonio and Alonso Nanclares, Lidia and Muelas Pascual, Santiago and Peña Sanchez, Jose Maria and Felipe Oroquieta, Javier de (2013). 3D segmentations of neuronal nuclei from confocal microscope image stacks. "Frontiers in Neuroanatomy", v. 7 ; pp. 1-10. ISSN 1662-5129. https://doi.org/10.3389/fnana.2013.00049.

Description

Title: 3D segmentations of neuronal nuclei from confocal microscope image stacks
Author/s:
  • La Torre, Antonio
  • Alonso Nanclares, Lidia
  • Muelas Pascual, Santiago
  • Peña Sanchez, Jose Maria
  • Felipe Oroquieta, Javier de
Item Type: Article
Título de Revista/Publicación: Frontiers in Neuroanatomy
Date: December 2013
ISSN: 1662-5129
Volume: 7
Subjects:
Freetext Keywords: 3D reconstruction, automatic segmentation, cerebral cortex, image processing, neuron
Faculty: Centro de Tecnología Biomédica (CTB) (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (1MB) | Preview

Abstract

In this paper, we present an algorithm to create 3D segmentations of neuronal cells from stacks of previously segmented 2D images. The idea behind this proposal is to provide a general method to reconstruct 3D structures from 2D stacks, regardless of how these 2D stacks have been obtained. The algorithm not only reuses the information obtained in the 2D segmentation, but also attempts to correct some typical mistakes made by the 2D segmentation algorithms (for example, under segmentation of tightly-coupled clusters of cells). We have tested our algorithm in a real scenario?the segmentation of the neuronal nuclei in different layers of the rat cerebral cortex. Several representative images from different layers of the cerebral cortex have been considered and several 2D segmentation algorithms have been compared. Furthermore, the algorithm has also been compared with the traditional 3D Watershed algorithm and the results obtained here show better performance in terms of correctly identified neuronal nuclei.

More information

Item ID: 31180
DC Identifier: http://oa.upm.es/31180/
OAI Identifier: oai:oa.upm.es:31180
DOI: 10.3389/fnana.2013.00049
Official URL: http://journal.frontiersin.org/article/10.3389/fnana.2013.00049/abstract
Deposited by: Memoria Investigacion
Deposited on: 13 Apr 2015 19:27
Last Modified: 13 Apr 2015 19:27
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM