Evidence map›Paper›PMID 33568775›Full record

ArticleCommunications biology2021

DeepACSON automated segmentation of white matter in 3D electron microscopy.

Ali Abdollahzadeh, Ilya Belevich, Eija Jokitalo, Alejandra Sierra, Jussi Tohka

Abstract read
In one paragraph

Article in Communications biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

5 authors.

Ali AbdollahzadehA. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland.ORCID http://orcid.org/0000-0001-6234-2012
Ilya BelevichElectron Microscopy Unit, Institute of Biotechnology, University of Helsinki, Helsinki, Finland.ORCID http://orcid.org/0000-0003-2190-4909
Eija JokitaloElectron Microscopy Unit, Institute of Biotechnology, University of Helsinki, Helsinki, Finland.ORCID http://orcid.org/0000-0002-4159-6934
Alejandra Sierra *A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland. alejandra.sierralopez@uef.fi.ORCID http://orcid.org/0000-0001-5399-2056
Jussi Tohka *A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland.ORCID http://orcid.org/0000-0002-1048-5860

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tracing the entirety of ultrastructures in large three-dimensional electron microscopy (3D-EM) images of the brain tissue requires automated segmentation techniques. Current segmentation techniques use deep convolutional neural networks (DCNNs) and rely on high-contrast cellular membranes and high-resolution EM volumes. On the other hand, segmenting low-resolution, large EM volumes requires methods to account for severe membrane discontinuities inescapable. Therefore, we developed DeepACSON, which performs DCNN-based semantic segmentation and shape-decomposition-based instance segmentation. DeepACSON instance segmentation uses the tubularity of myelinated axons and decomposes under-segmented myelinated axons into their constituent axons. We applied DeepACSON to ten EM volumes of rats after sham-operation or traumatic brain injury, segmenting hundreds of thousands of long-span myelinated axons, thousands of cell nuclei, and millions of mitochondria with excellent evaluation scores. DeepACSON quantified the morphology and spatial aspects of white matter ultrastructures, capturing nanoscopic morphological alterations five months after the injury.

Indexed as

Artificial IntelligenceImage Interpretation, Computer-AssistedImaging, Three-DimensionalMicroscopy, ElectronAnimalsBrain Injuries, TraumaticCell NucleusDisease Models, AnimalMaleMitochondriaNerve Fibers, MyelinatedPredictive Value of TestsRatsRats, Sprague-DawleyReproducibility of ResultsWhite Matter

Identifiers

PMID33568775
PMCPMC7876004

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.