Quantitative morphodynamic analysis of time-Lapse imaging by edge evolution tracking

Yuki Tsukada, Yuichi Sakumura, Shin Ishii

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

To perform morphodynamic profiling from time lapse images of neurite outgrowth, we developed an edge evolution tracking (EET) algorithm, by which cell boundary movements including an arbitrary complex boundary transition are quantified. This algorithm enables us to estimate temporal evolution of cellular edge, and thus to trace the transition of any objective edge movements. We show advantages of EET by comparing it with the other two methods on an artificial data set that imitates neural outgrowth. We also demonstrate the usefulness of our EET by applying it to a data set of time-lapse imaging of neural outgrowth. The results show verification of quantitative profiling for arbitrary complex cell boundary movements.

Original languageEnglish
Title of host publicationNeural Information Processing - 14th International Conference, ICONIP 2007, Revised Selected Papers
Pages817-826
Number of pages10
EditionPART 2
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event14th International Conference on Neural Information Processing, ICONIP 2007 - Kitakyushu, Japan
Duration: 2007 Nov 132007 Nov 16

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume4985 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other14th International Conference on Neural Information Processing, ICONIP 2007
Country/TerritoryJapan
CityKitakyushu
Period07/11/1307/11/16

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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