Evidence map›Paper›PMID 34129786›Full record

ArticleJournal of the Royal Society, Interface2021

An integrated platform to facilitate the calculation, validation and visualization of optical flow velocities in biological images.

Xianbin Yong, Cheng-Kuang Huang, Chwee Teck Lim

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Xianbin YongIntegrative Sciences and Engineering Programme, NUS Graduate School, National University of Singapore, Singapore.
Cheng-Kuang HuangMechanobiology Institute, National University of Singapore, Singapore.
Chwee Teck LimIntegrative Sciences and Engineering Programme, NUS Graduate School, National University of Singapore, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optical flow algorithms have seen poor adoption in the biological community compared with particle image velocimetry for quantifying cellular dynamics because of the lack of proper validation and an intuitive user interface. To address these challenges, we present OpFlowLab, an integrated platform that integrates our motion estimation workflow. Using routines in our workflow, we demonstrate that optical flow algorithms are more accurate than PIV in simulated images of the movement of nuclei. Qualitative assessment with actual nucleus images further supported this finding. Additionally, we show that refinement of the optical flow velocities is possible with a simple object-matching procedure, opening up the possibility of obtaining reasonable velocity estimates under less ideal imaging conditions. To visualize velocity fields, we employ artificial tracers to allow for the drawing of pathlines. Through the adoption of OpFlowLab, we are confident that optical flow algorithms will allow for the exploration of dynamic biological systems in greater accuracy and detail.

Indexed as

Optic FlowAlgorithmsBlood Flow VelocityRheologycollective cell migrationmotion estimationoptical flowparticle image velocimetry

Identifiers

PMID34129786
PMCPMC8205530

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.