title: Automatic segmentation of time-lapse microscopy images depicting a live Dharma embryo.
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.
authors.affiliation: Computational Biomedicine Lab, Department of Computer Science, University of Houston, Houston, TX 77204-3010, USA. eezacharia@gmail.com
authors.forename: Eleni
authors.initials: E
authors.lastname: Zacharia
authors.forename: Maria
authors.initials: M
authors.lastname: Bondesson
authors.forename: Anne
authors.initials: A
authors.lastname: Riu
authors.forename: Nicole A
authors.initials: NA
authors.lastname: Ducharme
authors.forename: Jan-Åke
authors.initials: JÅ
authors.lastname: Gustafsson
authors.forename: Ioannis A
authors.initials: IA
authors.lastname: Kakadiaris
mesh_terms: D000818:Animals; D001331:Automation; D002875:Chromosomes / Q000378:metabolism; D004625:Embryo, Nonmammalian / Q000033:anatomy & histology*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008856:Microscopy, Fluorescence / Q000379:methods*; D059008:Time-Lapse Imaging / Q000379:methods*; D015027:Zebrafish / Q000196:embryology*