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Automated identification of flagella from videomicroscopy via the medial axis transform

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...

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Autores principales: Walker, Benjamin J., Ishimoto, Kenta, Wheeler, Richard J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6428899/
https://www.ncbi.nlm.nih.gov/pubmed/30899085
http://dx.doi.org/10.1038/s41598-019-41459-9
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author Walker, Benjamin J.
Ishimoto, Kenta
Wheeler, Richard J.
author_facet Walker, Benjamin J.
Ishimoto, Kenta
Wheeler, Richard J.
author_sort Walker, Benjamin J.
collection PubMed
description 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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spelling pubmed-64288992019-03-28 Automated identification of flagella from videomicroscopy via the medial axis transform Walker, Benjamin J. Ishimoto, Kenta Wheeler, Richard J. Sci Rep Article 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. Nature Publishing Group UK 2019-03-21 /pmc/articles/PMC6428899/ /pubmed/30899085 http://dx.doi.org/10.1038/s41598-019-41459-9 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Walker, Benjamin J.
Ishimoto, Kenta
Wheeler, Richard J.
Automated identification of flagella from videomicroscopy via the medial axis transform
title Automated identification of flagella from videomicroscopy via the medial axis transform
title_full Automated identification of flagella from videomicroscopy via the medial axis transform
title_fullStr Automated identification of flagella from videomicroscopy via the medial axis transform
title_full_unstemmed Automated identification of flagella from videomicroscopy via the medial axis transform
title_short Automated identification of flagella from videomicroscopy via the medial axis transform
title_sort automated identification of flagella from videomicroscopy via the medial axis transform
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6428899/
https://www.ncbi.nlm.nih.gov/pubmed/30899085
http://dx.doi.org/10.1038/s41598-019-41459-9
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