cellpiv is a Python code to analyze microscopy images of cellular monolayers using openPIV (
The code builds on Particle Image Velocimetry (PIV) applied to image pairs, and extends this analysis to entire movies and full datasets - i.e., multiple fields of view - processed in parallel.
The package uses the resulting PIV fields to compute higher-level quantities such as RMS velocity, correlation functions, and alignment maps across the entire dataset.
The code is used in association with the following publication:
Jasmin Kaivola, Karolina Punovuori, Megan R. Chastney, Hind Abdo, Gautier Follain, Mathilde Mathieu, Omkar Joshi, Yekaterina A. Miroshnikova, Fabian Krautgasser, Jasmin Di Franco, James R. W. Conway, Sofia Held, Fabien Bertillot, Jaana Hagström, Antti Mäkitie, Heikki Irjala, Sami Ventelä, Hellyeh Hamidi, Giorgio Scita, Roberto Cerbino, Sara A. Wickström, Johanna Ivaska (2026). Restoring the tumour mechanophenotype of vocal fold cancer reverts its malignant properties. Nat. Mater., no. 1 (2026): 1-15.
If you use this code, please cite the publication above.
cellpiv is available under the GNU GPL-3.0 license.
cellpiv was developed by Fabian Krautgasser and Jasmin Di Franco.
SomexLab: https://somexlab.github.io/