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Updated: Sep 1, 2025
A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells
Published on: September 28, 2019
Griottes: a generalist tool for network generation from segmented tissue images
Gustave Ronteix1,2, Andrey Aristov1, Valentin Bonnet1,2
1Institut Pasteur, Université Paris Cité, Physical microfluidics and Bioengineering, Paris, F-75015, France.
Background:
Microscopy techniques and image segmentation algorithms have improved dramatically this decade, leading to an ever increasing amount of biological images and a greater reliance on imaging to investigate biological questions. This has created a need for methods to extract the relevant information on the behaviors of cells and their interactions, while reducing the amount of computing power required to organize this information.
Results:
This task can be performed by using a network representation in which the cells and their properties are encoded in the nodes, while the neighborhood interactions are encoded by the links. Here, we introduce Griottes, an open-source tool to build the "network twin" of 2D and 3D tissues from segmented microscopy images. We show how the library can provide a wide range of biologically relevant metrics on individual cells and their neighborhoods, with the objective of providing multi-scale biological insights. The library's capacities are demonstrated on different image and data types.
Conclusions:
This library is provided as an open-source tool that can be integrated into common image analysis workflows to increase their capacities.
