Image analysis of self-organized multicellular patterns

Christian Thies*, Galina Khachaturyan, Assaf Zemel, Ralf Kemkemer

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Analysis of multicellular patterns is required to understand tissue organizational processes. By using a multi-scale object oriented image processing method, the spatial information of cells can be extracted automatically. Instead of manual segmentation or indirect measurements, such as general distribution of contrast or flow, the orientation and distribution of individual cells is extracted for quantitative analysis. Relevant objects are identified by feature queries and no low-level knowledge of image processing is required.

Original languageAmerican English
Pages (from-to)523-527
Number of pages5
JournalCurrent Directions in Biomedical Engineering
Volume2
Issue number1
DOIs
StatePublished - Sep 2016

Bibliographical note

Publisher Copyright:
© 2016 Christian Thies et al., licensee De Gruyter.

Keywords

  • Cell segmentation
  • Image analysis
  • Object extraction
  • Phase contrast micrographs
  • Spatial information
  • Tissue organization

Fingerprint

Dive into the research topics of 'Image analysis of self-organized multicellular patterns'. Together they form a unique fingerprint.

Cite this