A global spatial similarity optimization scheme to track large numbers of dendritic spines in time-lapse confocal microscopy

Qing Li, Zhigang Deng, Yong Zhang, Xiaobo Zhou, U. Valentin Nagerl, Stephen T C Wong

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

Dendritic spines form postsynaptic contact sites in the central nervous system. The rapid and spontaneous morphology changes of spines have been widely observed by neurobiologists. Determining the relationship between dendritic spine morphology change and its functional properties such as memory learning is a fundamental yet challenging problem in neurobiology research. In this paper, we propose a novel algorithm to track the morphology change of multiple spines simultaneously in time-lapse neuronal images based on nonrigid registration and integer programming. We also propose a robust scheme to link disappearing-and-reappearing spines. Performance comparisons with other state-of-the-art cell and spine tracking algorithms, and the ground truth show that our approach is more accurate and robust, and it is capable of tracking a large number of neuronal spines in time-lapse confocal microscopy images.

Original languageEnglish (US)
Article number5613939
Pages (from-to)632-641
Number of pages10
JournalIEEE Transactions on Medical Imaging
Volume30
Issue number3
DOIs
StatePublished - Mar 2011

Keywords

  • Dendritic spine
  • free form deformation
  • global similarity
  • integer programming
  • time-lapse images

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Radiological and Ultrasound Technology
  • Software

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