Evidence map›Paper›PMID 36506593›Full record

ArticleFrontiers in neural circuits2022

Igneous: Distributed dense 3D segmentation meshing, neuron skeletonization, and hierarchical downsampling.

William Silversmith, Aleksandar Zlateski, J Alexander Bae, Ignacio Tartavull, Nico Kemnitz, Jingpeng Wu, H Sebastian Seung

Abstract read
In one paragraph

Article in Frontiers in neural circuits, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
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  4. PyReconstruct: A fully open-source, collaborative successor to Reconstruct.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  5. Article
  6. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

William SilversmithPrinceton Neuroscience Institute, Princeton University, Princeton, NJ, United States.
Aleksandar ZlateskiPrinceton Neuroscience Institute, Princeton University, Princeton, NJ, United States.
J Alexander BaePrinceton Neuroscience Institute, Princeton University, Princeton, NJ, United States.
Ignacio TartavullPrinceton Neuroscience Institute, Princeton University, Princeton, NJ, United States.
Nico KemnitzPrinceton Neuroscience Institute, Princeton University, Princeton, NJ, United States.
Jingpeng WuPrinceton Neuroscience Institute, Princeton University, Princeton, NJ, United States.
H Sebastian SeungPrinceton Neuroscience Institute, Princeton University, Princeton, NJ, United States.

Funding

Subcortical Neural Coding and DynamicsU19NS104648 · NINDS · PRINCETON UNIVERSITY · PI BRODY, CARLOS D · 2017 to 2021
$15.3M
Collaboratory for atlasing cell type anatomy in the female and male mouse brainU01MH114824 · NIMH · COLD SPRING HARBOR LABORATORY · PI MITRA, PARTHA PRATIM · 2017 to 2021
$11.7M
Towards integrated 3D reconstruction of whole human brains at subcellular resolutionU01MH117072 · NIMH · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI CHUNG, KWANGHUN · 2018 to 2022
$8.8M
Circuit Mechanisms Underlying Persistent Activity in a Neural IntegratorR01EY027036 · NEI · WEILL MEDICAL COLL OF CORNELL UNIV · PI Emre R Aksay, MARK S GOLDMAN · 2016 to 2026
$6.4M
Circuit Mechanisms Underlying Learned Changes in Persistent Neural ActivityR01NS104926 · NINDS · WEILL MEDICAL COLL OF CORNELL UNIV · PI AKSAY, EMRE R, GOLDMAN, MARK S · 2018 to 2022
$4.1M
Crowdsourcing the Fly ConnectomeRF1MH117815 · NIMH · PRINCETON UNIVERSITY · PI MURTHY, MALA, SEUNG, HYUNJUNE SEBASTIAN · 2018 to 2018
$3.3M
NEI NIH HHS R01 EY027036NIMH NIH HHS RF1 MH117815NIMH NIH HHS U01 MH114824NIMH NIH HHS U01 MH117072NINDS NIH HHS R01 NS104926NINDS NIH HHS U19 NS104648
6 · The paper itself

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.

Indexed as

Imaging, Three-DimensionalNeuronsImage Processing, Computer-AssistedInformation Storage and RetrievalMicroscopy, Electroncloud computingcompressionconnectomicsdistributed computingimage processingmeshingneuroscienceskeletonization

Identifiers

PMID36506593
PMCPMC9732676

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.