The Mouse Retina Analysis packages contains scripts for analyzing and segmenting individual cone cells from immunofluorescence images of mouse retinas.
Images are analyzed using a custom parallel image processing pipeline in Biospark. Briefly, each fluorescence channel is first normalized and filtered to remove small bright features. Then, each remaining peak in fluorescence intensity is identified and an independent active contour segmentation is performed starting from the peak. If the resulting contour passes validation checks it is included in the list of segmented cone cells for the channel. Finally, cell boundaries are reconciled across both channels to obtain a complete list of identified cone cells. Full details are given in the SI Methods of the referenced publication.
Kiara C. Eldred, Cameron Avelis, Robert J. Johnston Jr., and Elijah Roberts.
Modeling binary and graded cell fate patterning in the mouse retina.
If you have questions about the software please contact firstname.lastname@example.org.
2019.05.17 - Initial release
This package contains a Jupyter notebook for running the segmentation and analyses described in the referenced publication. In order to use this notebook, you must already have the Biospark package correctly installed on your computer or be using the Biospark virtual machine image distributed from the Roberts lab website.
To run the Jupyter notebook after downloading and extracting the archive:
cd notebooks jupyter notebook
Then launch the
segmentation_analysis.ipynb file in the Jupyter browser.
The code archive contains all of the code needed to run the segmentation. Also available are the raw retina images from the referenced publication.