Constructing neuronal structure from 3D confocal microscopic images

Ping Chang Lee, Hsiu Ming Chang, Chih Yang Lin, Ann Shyn Chiang, Yu-Tai Ching*

*Corresponding author for this work

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

A semiautomatic method, based on the gradient vector flow (GVF) snake, to construct the neuronal structure from 3D confocal microscopic images is presented. A single neuron can be labeled by using green fluorescent protein (GFP) such that the 3D neuronal structure can be visualized in a stack of confocal microscopic images. To construct the neuronal structure, we traced a target fiber by providing a rough initial path to approximate that fiber. The path is then deformed under the gradient vector field to converge to the centerline of the fiber by using the GVF snake method. Using our developed software, a neuronal structural can be efficiently reconstructed and the tracing results can be reduced to the tree structure of the neuron. Given the tree structure of the neuron, quantitative information can be derived and further analysis can be carried out.

Original languageEnglish
Pages (from-to)1-6
Number of pages6
JournalJournal of Medical and Biological Engineering
Volume29
Issue number1
StatePublished - 1 Mar 2009

Keywords

  • Confocal microscopy
  • Gradient vector flow (GVF) snake
  • Green fluorescent protein (GFP)
  • Neuron tracing
  • Tree structure

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