Segmentation of Developing Human Embryo in Time-lapse Microscopy

Being able to efficiently segment a developing embryo from background clutter constitutes an important step in automated monitoring of human embryonic cells. State-of-the-art automatic segmentation methods remain ill-suited to handle the complex behavior and morphological variance of non-stained embryos. By contrast, while effective, manual approaches are impractically time-consuming. In this paper, we introduce an automated approach to segment human embryo in early-stage development from a sequence of dark field microscopy images. In particular, we express segmentation as an energy minimization problem, which can be solved efficiently via graph-cuts or dynamic programming. Our experiments on twenty embryo sequences demonstrates that our method can successfully segment complex and irregular embryo structures in time-lapse microscopy (TLM) sequences.


Published in:
International Symposium on Biomedical Imaging
Presented at:
International Symposium on Biomedical Imaging (ISBI)
Year:
2016
Publisher:
New York, IEEE
ISBN:
978-1-4799-2349-6; 978-1-4799-2350-2
Laboratories:




 Record created 2017-01-24, last modified 2018-01-28


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