Evidence map›Paper›PMID 26306866›Full record

ArticleNeuroinformatics2016

TReMAP: Automatic 3D Neuron Reconstruction Based on Tracing, Reverse Mapping and Assembling of 2D Projections.

Zhi Zhou, Xiaoxiao Liu, Brian Long, Hanchuan Peng

Abstract read
PubMed Publisher
In one paragraph

Article in Neuroinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. DNeuroMAT: A Deep-Learning-Based Neuron Morphology Analysis Toolbox.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. Tracing weak neuron fibers.Bioinformatics (Oxford, England) · 2023
    Article
  10. Review
  11. Article
  12. Review
  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

4 authors.

Zhi ZhouAllen Institute for Brain Science, Seattle, WA, USA.
Xiaoxiao LiuAllen Institute for Brain Science, Seattle, WA, USA.
Brian LongAllen Institute for Brain Science, Seattle, WA, USA.
Hanchuan PengAllen Institute for Brain Science, Seattle, WA, USA. hanchuanp@alleninstitute.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Efficient and accurate digital reconstruction of neurons from large-scale 3D microscopic images remains a challenge in neuroscience. We propose a new automatic 3D neuron reconstruction algorithm, TReMAP, which utilizes 3D Virtual Finger (a reverse-mapping technique) to detect 3D neuron structures based on tracing results on 2D projection planes. Our fully automatic tracing strategy achieves close performance with the state-of-the-art neuron tracing algorithms, with the crucial advantage of efficient computation (much less memory consumption and parallel computation) for large-scale images.

Indexed as

SoftwareAlgorithmsAnimalsBrainHumansImaging, Three-DimensionalNeuroanatomical Tract-Tracing TechniquesNeurons2D ProjectionNeuron reconstructionReverse mappingVaa3DVirtual finger

Identifiers

What OpenQuestion holds

Textmetadata
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.