Here, we submit the code to analyze the *Drosophila* Salivary Gland tissues. To reproduce this analysis, we recommend you to go to the commit where the release happened.
https://github.com/ComplexOrganizationOfLivingMatter/LimeSeg_Pipeline/releases
<h3> Initial segmentation with LimeSeg </h3>
It is the main repository for the project "Epithelial laws" by Gomez-Galvez et al. The input of this project is the output of the LimeSeg plugin of FIJI (http://imagej.net/LimeSeg/).
The steps of this project are explained on: https://github.com/ComplexOrganizationOfLivingMatter/LimeSeg_Pipeline/blob/master/LimeSegTutorial.md#step-3-matlabs-refining-process.
Here, we explained how to run this repository and all the data necessary to do so.
IMPORTANT This project depends on code from https://github.com/ComplexOrganizationOfLivingMatter/Epithelia3D
<h3> Postprocessing and curation of LimeSeg output </h3>
Go to: https://github.com/ComplexOrganizationOfLivingMatter/Processing3DSegmentation/releases/tag/1.2022
Run main.m and follow the instructions there.
<h3> Deep learning segmentation with 3D-U-Net </h3>
3D-U-Net CNN (Franco-Barranco et al., 15 2021),
Follow instructions on https://github.com/danifranco/EM_Image_Segmentation. We used the configuration file to obtain the cell outline from unseen images from E-cad mutant: unet_3d_glands_general_da.yaml
Using the cell outline as input, we, then, obtain the instance segmentation of the images using PlantSeg segmentation module (A. Wolny et al. 2020).
<h3> Feature extraction of segmented Salivary Gland </h3>
https://github.com/ComplexOrganizationOfLivingMatter/SalivaryGlands/releases/tag/1.2022
**Optional: Obtain 'flatten' E-cad muntant Salivary Glands**
main_flattenGlands.m
**Mandatory: Obtain general features**
mainFeaturesExtraction.m
main_divideGlandSR.m
mainFeaturesExtraction_dividedGlandsBySR.m
