siboles / pcm_segmenter Goto Github PK

This archive contains the data and custom Python package to reproduce the image processing, segmentation, and analysis conducted for the publication "The Protective Function of Directed Asymmetry in the Pericellular Matrix Enveloping Chondrocytes." Annals of Biomedical Engineering. DOI: 10.1007/s10439-021-02900-1.

The Python package utilizes the conda package manager for dependency resolution. We recommend installing the miniforge3 implementation of conda from https://conda-forge.org/miniforge/

After conda installation first add the siboles channel by executing:

conda config --add channels siboles

If you did not install miniforge3, you may also need to add the conda-forge channel with:

conda config --add channels conda-forge

One can then create an isolated conda environment with all necessary dependencies with the command:

conda create -n NAME_OF_ENVIRONMENT pycellanalyst pydantic pyyaml

where, NAME_OF_ENVIRONMENT, is the user's choice. To use the pcm_segmenter Python package the conda environment must be activated with:

conda activate NAME_OF_ENVIRONMENT

Optionally, the pcm_segmenter package can be installed for system-wide execution (with the conda environment activated) by running:

python setup.py install

The study dataset can be retrieved from:

Extract this to the top-level of this repository.

The study can then be reproduced by navigating to the scripts directory:

cd scripts

and running the segmentation and analysis with

python manuscript_analysis.py

and the post-processing with

python manuscript_postprocess.py

This will generate a results directory tree with the resulting VTK files for each specimen/region in appropriate sub-folders. At the root level of the results directory, Excel files containing the analysis results for each specimen will be created. Finally, after running manuscript_postprocess.py, manuscript_analyses_aggregate.xlsx will be written with the measurements for all cells aggregated into a single file.