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.<br> 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.<br> 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. <strong>Credits, contact, citations</strong><br> If you use this dataset, please cite the published version of the following preprint: <br> <em>Ichbiah, S., Delbary, F., McDougall, A., Dumollard, R., &amp; Turlier, H. (2023). Embryo mechanics cartography: inference of 3D force atlases from fluorescence microscopy. bioRxiv, 2023-04. </em>https://doi.org/10.1101/2023.04.12.536641<br> <br> We hope that this dataset may be useful to benchmark future 3D force inference methods.<br> If you have any question on this dataset, please contact Hervé Turlier. <strong>License</strong><br> Copyright (c) 2023 Turlier Lab - https://www.turlierlab.com/<br> This dataset is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License.