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Updated: Aug 17, 2025

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells
Published on: September 28, 2019
Igneous: Distributed dense 3D segmentation meshing, neuron skeletonization, and hierarchical downsampling
William Silversmith1, Aleksandar Zlateski1,2, J Alexander Bae1,3
1Princeton Neuroscience Institute, Princeton University, Princeton, NJ, United States.
Abstract:
Three-dimensional electron microscopy images of brain tissue and their dense segmentations are now petascale and growing. These volumes require the mass production of dense segmentation-derived neuron skeletons, multi-resolution meshes, image hierarchies (for both modalities) for visualization and analysis, and tools to manage the large amount of data. However, open tools for large-scale meshing, skeletonization, and data management have been missing. Igneous is a Python-based distributed computing framework that enables economical meshing, skeletonization, image hierarchy creation, and data management using cloud or cluster computing that has been proven to scale horizontally. We sketch Igneous's computing framework, show how to use it, and characterize its performance and data storage.
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