A new annotated dataset of zebrafish embryo image sequences enables a spatiotemporal transformer to classify fertility at 98% accuracy and detect compound-induced malformations at 92% accuracy.
In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2014)
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Automated Detection of Abnormalities in Zebrafish Development
A new annotated dataset of zebrafish embryo image sequences enables a spatiotemporal transformer to classify fertility at 98% accuracy and detect compound-induced malformations at 92% accuracy.