Simulation dataset to benchmark 3D force inference methods

Dataset of 47 artificial images (.tif) and corresponding segmentation masks (.tif), generated from simulations of foam-like cell structures (early embryos) of various cell numbers (2 to 11), cell sizes and interfacial tensions.
The ground truth simulation tensions and pressures to be inferred are provided as Numpy arrays (.npy).

This dataset was used to benchmark a method to infer cellular forces in 3D from microscopy images of multicellular contours, that is available on https://github.com/VirtualEmbryo/foambryo.
Non-manifold multimaterial meshes corresponding to artificial microscopy images are also provided as binary files (.rec) and may be opened with our delaunay-watershed Python code, available on https://github.com/VirtualEmbryo/delaunay-watershed.

Credits, contact, citations
If you use this dataset, please cite the published version of the following preprint: 
Ichbiah, S., Delbary, F., McDougall, A., Dumollard, R., & Turlier, H. (2023). Embryo mechanics cartography: inference of 3D force atlases from fluorescence microscopy. bioRxiv, 2023-04. https://doi.org/10.1101/2023.04.12.536641

We hope that this dataset may be useful to benchmark future 3D force inference methods.
If you have any question on this dataset, please contact Hervé Turlier.

License
Copyright (c) 2023 Turlier Lab - https://www.turlierlab.com/
This dataset is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License.