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Published on: September 9, 2020
Automatic segmentation of time-lapse microscopy images depicting a live Dharma embryo
Eleni Zacharia1, Maria Bondesson, Anne Riu
1Computational Biomedicine Lab, Department of Computer Science, University of Houston, Houston, TX 77204-3010, USA. eezacharia@gmail.com
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.

