Evidence map›Paper›PMID 28493862›Full record

ArticlePLoS computational biology2017

FIMTrack: An open source tracking and locomotion analysis software for small animals.

Benjamin Risse, Dimitri Berh, Nils Otto, Christian Klämbt, Xiaoyi Jiang

Abstract read
In one paragraph

Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing 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

50 citing papers in PubMed.

  1. Article
  2. Multiple Scales of Coordination along the Body Axis duringThe Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
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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

5 authors.

Benjamin RisseSchool of Informatics, University of Edinburgh, Edinburgh, Scotland, United Kingdom.ORCID 0000-0001-5691-4029
Dimitri BerhFaculty of Mathematics and Computer Science, University of Münster, Münster, Germany.
Nils OttoDepartment of Behaviour and Neuronal Biology, University of Münster, Münster, Germany.
Christian KlämbtDepartment of Behaviour and Neuronal Biology, University of Münster, Münster, Germany.ORCID 0000-0002-6349-5800
Xiaoyi JiangFaculty of Mathematics and Computer Science, University of Münster, Münster, Germany.ORCID 0000-0001-7678-9528

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Imaging and analyzing the locomotion behavior of small animals such as Drosophila larvae or C. elegans worms has become an integral subject of biological research. In the past we have introduced FIM, a novel imaging system feasible to extract high contrast images. This system in combination with the associated tracking software FIMTrack is already used by many groups all over the world. However, so far there has not been an in-depth discussion of the technical aspects. Here we elaborate on the implementation details of FIMTrack and give an in-depth explanation of the used algorithms. Among others, the software offers several tracking strategies to cover a wide range of different model organisms, locomotion types, and camera properties. Furthermore, the software facilitates stimuli-based analysis in combination with built-in manual tracking and correction functionalities. All features are integrated in an easy-to-use graphical user interface. To demonstrate the potential of FIMTrack we provide an evaluation of its accuracy using manually labeled data. The source code is available under the GNU GPLv3 at https://github.com/i-git/FIMTrack and pre-compiled binaries for Windows and Mac are available at http://fim.uni-muenster.de.

Indexed as

SoftwareAlgorithmsAnimalsCaenorhabditis elegansComputational BiologyImage Processing, Computer-AssistedLocomotion

Identifiers

PMID28493862
PMCPMC5444858

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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.