This repository contains code for the analysis of 2DT and 3DT live imaging data. Typically, the processing of such data in this framework consists of the following steps:
- compression of the images into hdf5 format and illumination correction
- segmentation of objects in the images
- measurement of features (e.g. morphology features or intensity features) based on the segmentations
For each of these steps, the user will have to define suitable parameters. These parameters are then saved in a settings file that is specific for each experiment and which will be used in the final image processing.
You will need to install everything on the cluster as well as locally (to do some parameter tuning).
- Create a virtual python environment
- Activate your virtual python environment
- Install lca from github
- The tracking in this framework is formulated as a linear assignment problem. To solve this problem we use a very useful Cython implementation of the auction algorithm (https://github.com/OllieBoyne/sslap).
pip install git+https://github.com/OllieBoyne/sslap.git
conda create -n lca python=3.9
conda activate lca
pip install git+https://github.com/adrtsc/lca.git