Recognition and analysis of cell nuclear phases for high-content screening based on morphological features

Donggang Yu, Tuan D. Pham, Xiaobo Zhou, Stephen T.C. Wong

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Automated analysis of molecular images has increasingly become an important research in computational life science. In this paper some new and efficient algorithms for recognizing and analyzing cell phases of high-content screening are presented. The conceptual frameworks are based on the morphological features of cell nuclei. The useful preprocessing includes: smooth following and linearization; extraction of morphological structural points; shape recognition based morphological structure; issue of touching cells for cell separation and reconstruction. Furthermore, the novel detecting and analyzing strategies of feed-forward and feed-back of cell phases are proposed based on gray feature, cell shape, geometrical features and difference information of corresponding neighbor frames. Experiment results tested the efficiency of the new method.

Original languageEnglish (US)
Pages (from-to)498-508
Number of pages11
JournalPattern Recognition
Issue number4
StatePublished - Apr 2009


  • Cell screening
  • Feature extraction
  • Feed-back detection
  • Feed-forward detection
  • Morphological feature
  • Normal cellular cycle
  • Nuclei phases
  • Shape recognition

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing


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