ArticleScientific reports2019
Automated identification of flagella from videomicroscopy via the medial axis transform.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- Embodied behavioural complexity in a ciliated microorganism.Nature communications · 2026Article
- Axonemal dynein contributions to flagellar beat types and waveforms.bioRxiv : the preprint server for biology · 2025Article
- Proteins with proximal-distal asymmetries in axoneme localisation control flagellum beat frequency.Nature communications · 2025Article
- Revealing Rotational Characteristics of the Uniflagellate Mutant ofmicroPublication biology · 2025Article
- Intraflagellar transport speed is sensitive to genetic and mechanical perturbations to flagellar beating.The Journal of cell biology · 2024Article
- Modelling Motility: The Mathematics of Spermatozoa.Frontiers in cell and developmental biology · 2021Review
- Computer-assisted beat-pattern analysis and the flagellar waveforms of bovine spermatozoa.Royal Society open science · 2020Article
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Authors and funding
3 authors at 2 institutions in 3 countries.
Funding
Abstract
Ubiquitous in eukaryotic organisms, the flagellum is a well-studied organelle that is well-known to be responsible for motility in a variety of organisms. Commonly necessitated in their study is the capability to image and subsequently track the movement of one or more flagella using videomicroscopy, requiring digital isolation and location of the flagellum within a sequence of frames. Such a process in general currently requires some researcher input, providing some manual estimate or reliance on an experiment-specific heuristic to correctly identify and track the motion of a flagellum. Here we present a fully-automated method of flagellum identification from videomicroscopy based on the fact that the flagella are of approximately constant width when viewed by microscopy. We demonstrate the effectiveness of the algorithm by application to captured videomicroscopy of Leishmania mexicana, a parasitic monoflagellate of the family Trypanosomatidae. ImageJ Macros for flagellar identification are provided, and high accuracy and remarkable throughput are achieved via this unsupervised method, obtaining results comparable in quality to previous studies of closely-related species but achieved without the need for precursory measurements or the development of a specialised heuristic, enabling in general the automated generation of digitised kinematic descriptions of flagellar beating from videomicroscopy.
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Registered trials
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.