English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  RoboEM: automated 3D flight tracing for synaptic-resolution connectomics

Schmidt, M., Motta, A., Sievers, M., & Helmstaedter, M. (2024). RoboEM: automated 3D flight tracing for synaptic-resolution connectomics. Nat Methods. doi: 10.1038/s41592-024-02226-5.

Item is

Files

show Files

Locators

show
hide
Description:
-
OA-Status:
Gold

Creators

show
hide
 Creators:
Schmidt, Martin1, Author
Motta , Alessandro1, Author
Sievers, Meike1, 2, Author
Helmstaedter, Moritz1, Author           
Affiliations:
1Connectomics Department, Max Planck Institute for Brain Research, Max Planck Society, ou_2461695              
2Faculty of Science, Radboud University, Nijmegen, the Netherlands., ou_persistent22              

Content

show
hide
Free keywords: Computational neuroscience Mouse Synaptic transmission
 Abstract: Mapping neuronal networks from three-dimensional electron microscopy (3D-EM) data still poses substantial reconstruction challenges, in particular for thin axons. Currently available automated image segmentation methods require manual proofreading for many types of connectomic analysis. Here we introduce RoboEM, an artificial intelligence-based self-steering 3D 'flight' system trained to navigate along neurites using only 3D-EM data as input. Applied to 3D-EM data from mouse and human cortex, RoboEM substantially improves automated state-of-the-art segmentations and can replace manual proofreading for more complex connectomic analysis problems, yielding computational annotation cost for cortical connectomes about 400-fold lower than the cost of manual error correction.

Details

show
hide
Language(s): eng - English
 Dates: 2022-09-082024-02-262024-03-21
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41592-024-02226-5
PMID: 38514779
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Nat Methods
  Abbreviation : Nat Methods
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: New York, NY : Nature Publishing Group
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: ISSN: 1548-7091
CoNE: https://pure.mpg.de/cone/journals/resource/111088195279556