Automatic segmentation of time-lapse microscopy images depicting a live Dharma embryo.

Eleni Zacharia, Maria Bondesson, Anne Riu, Nicole A. Ducharme, Jan-Ake Gustafsson, Ioannis A. Kakadiaris

Research output: Contribution to journalArticle

Abstract

Biological inferences about the toxicity of chemicals reached during experiments on the zebrafish Dharma embryo can be greatly affected by the analysis of the time-lapse microscopy images depicting the embryo. Among the stages of image analysis, automatic and accurate segmentation of the Dharma embryo is the most crucial and challenging. In this paper, an accurate and automatic segmentation approach for the segmentation of the Dharma embryo data obtained by fluorescent time-lapse microscopy is proposed. Experiments performed in four stacks of 3D images over time have shown promising results.

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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