Medaka embryo in 96 well plate - Widefield Brightfield

Submitted by LThomas on Mon, 04/29/2019 - 12:18

102 hpf medaka embryos in 96 well plate (4 embryo/well) - brightfield - 2X magnification - ACQUIFER Imaging Machine

Gierten, Jakob, et al. "Automated high-throughput heart rate measurement in medaka and zebrafish embryos under physiological conditions." bioRxiv (2019): 548594.

Used as benchmark dataset for Multi-Template-Matching by Thomas and Gehrig 

See implementation in Fiji https://github.com/LauLauThom/MultipleTemplateMatching


Quantitative Criterion Acquisition Network (QCA Net) performs instance segmentation of 3D fluorescence microscopic images. QCA Net consists of Nuclear Segmentation Network (NSN) that learned nuclear segmentation task and Nuclear Detection Network (NDN) that learned nuclear identification task. QCA Net performs instance segmentation of the time-series 3D fluorescence microscopic images at each time point, and the quantitative criteria for mouse development are extracted from the acquired time-series segmentation image. The detailed information on this program is described in our manuscript posted on bioRxiv.

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Normalize the orientation of the images of the Zebrafish embryos.

In the documentation webpage, the aim of the workflow is to normalize the orientation of the images of the Zebrafish embryos, find the point of injection of tumor cells and measure the distribution of Cy3 stained tumor foci.

ImageJ macro implementation of the Workflow described in Ghotra et al (2012). Note that currently only the angle and orientation normalization is implemented in this version.

Sample images are linked in the documentation webpage. 

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