Single cell annotations in 3D bacterial biofilms of Vibrio cholerae

This repository contains the data to reproduce the study Single-cell segmentation in bacterial biofilms with optimized convolutional neural networks enables tracking of cell lineages and measurements of growth rates by Jelli, Ohmura, Netter, et al. It contains the following four subfolders:   - training-data-from-experimentally-acquired-images: the dataset that was created to train segmentation models - trained-models: contains five models trained on the trainind dataset to be used for predictions - segmentation-predictions-for-different-species: segmentations based on a trained model on biofilms of different species - training-data-synthetic: Synthetic microscope images and their corresponding label images together with scripts to create the data