A computational framework for studying neuron morphology from in vitro high content neuron-based screening

Yue Huang, Xiaobo Zhou, Benchun Miao, Marta Lipinski, Yong Zhang, Fuhai Li, Alexei Degterev, Junying Yuan, Guangshu Hu, Stephen T.C. Wong

Research output: Contribution to journalArticle

10 Scopus citations

Abstract

High content neuron image processing is considered as an important method for quantitative neurobiological studies. The main goal of analysis in this paper is to provide automatic image processing approaches to process neuron images for studying neuron mechanism in high content screening. In the nuclei channel, all nuclei are segmented and detected by applying the gradient vector field based watershed. Then the neuronal nuclei are selected based on the soma region detected in neurite channel. In neurite images, we propose a novel neurite centerline extraction approach using the improved line-pixel detection technique. The proposed neurite tracing method can detect the curvilinear structure more accurately compared with the current existing methods. An interface called NeuriteIQ based on the proposed algorithms is developed finally for better application in high content screening.

Original languageEnglish (US)
Pages (from-to)299-309
Number of pages11
JournalJournal of Neuroscience Methods
Volume190
Issue number2
DOIs
StatePublished - Jul 2010

Keywords

  • Branch area
  • High content screening
  • Line-pixel detection
  • Microscopy image
  • Neurite outgrowth
  • Nuclei segmentation

ASJC Scopus subject areas

  • Neuroscience(all)

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