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Automated identification of insect vectors of Chagas disease in Brazil and Mexico: the Virtual Vector Lab

Identification of arthropods important in disease transmission is a crucial, yet difficult, task that can demand considerable training and experience. An important case in point is that of the 150+ species of Triatominae, vectors of Trypanosoma cruzi, causative agent of Chagas disease across the Ame...

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Autores principales: Gurgel-Gonçalves, Rodrigo, Komp, Ed, Campbell, Lindsay P., Khalighifar, Ali, Mellenbruch, Jarrett, Mendonça, Vagner José, Owens, Hannah L., de la Cruz Felix, Keynes, Peterson, A Townsend, Ramsey, Janine M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5398287/
https://www.ncbi.nlm.nih.gov/pubmed/28439451
http://dx.doi.org/10.7717/peerj.3040
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author Gurgel-Gonçalves, Rodrigo
Komp, Ed
Campbell, Lindsay P.
Khalighifar, Ali
Mellenbruch, Jarrett
Mendonça, Vagner José
Owens, Hannah L.
de la Cruz Felix, Keynes
Peterson, A Townsend
Ramsey, Janine M.
author_facet Gurgel-Gonçalves, Rodrigo
Komp, Ed
Campbell, Lindsay P.
Khalighifar, Ali
Mellenbruch, Jarrett
Mendonça, Vagner José
Owens, Hannah L.
de la Cruz Felix, Keynes
Peterson, A Townsend
Ramsey, Janine M.
author_sort Gurgel-Gonçalves, Rodrigo
collection PubMed
description Identification of arthropods important in disease transmission is a crucial, yet difficult, task that can demand considerable training and experience. An important case in point is that of the 150+ species of Triatominae, vectors of Trypanosoma cruzi, causative agent of Chagas disease across the Americas. We present a fully automated system that is able to identify triatomine bugs from Mexico and Brazil with an accuracy consistently above 80%, and with considerable potential for further improvement. The system processes digital photographs from a photo apparatus into landmarks, and uses ratios of measurements among those landmarks, as well as (in a preliminary exploration) two measurements that approximate aspects of coloration, as the basis for classification. This project has thus produced a working prototype that achieves reasonably robust correct identification rates, although many more developments can and will be added, and—more broadly—the project illustrates the value of multidisciplinary collaborations in resolving difficult and complex challenges.
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spelling pubmed-53982872017-04-24 Automated identification of insect vectors of Chagas disease in Brazil and Mexico: the Virtual Vector Lab Gurgel-Gonçalves, Rodrigo Komp, Ed Campbell, Lindsay P. Khalighifar, Ali Mellenbruch, Jarrett Mendonça, Vagner José Owens, Hannah L. de la Cruz Felix, Keynes Peterson, A Townsend Ramsey, Janine M. PeerJ Entomology Identification of arthropods important in disease transmission is a crucial, yet difficult, task that can demand considerable training and experience. An important case in point is that of the 150+ species of Triatominae, vectors of Trypanosoma cruzi, causative agent of Chagas disease across the Americas. We present a fully automated system that is able to identify triatomine bugs from Mexico and Brazil with an accuracy consistently above 80%, and with considerable potential for further improvement. The system processes digital photographs from a photo apparatus into landmarks, and uses ratios of measurements among those landmarks, as well as (in a preliminary exploration) two measurements that approximate aspects of coloration, as the basis for classification. This project has thus produced a working prototype that achieves reasonably robust correct identification rates, although many more developments can and will be added, and—more broadly—the project illustrates the value of multidisciplinary collaborations in resolving difficult and complex challenges. PeerJ Inc. 2017-04-18 /pmc/articles/PMC5398287/ /pubmed/28439451 http://dx.doi.org/10.7717/peerj.3040 Text en ©2017 Gurgel-Gonçalves et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Entomology
Gurgel-Gonçalves, Rodrigo
Komp, Ed
Campbell, Lindsay P.
Khalighifar, Ali
Mellenbruch, Jarrett
Mendonça, Vagner José
Owens, Hannah L.
de la Cruz Felix, Keynes
Peterson, A Townsend
Ramsey, Janine M.
Automated identification of insect vectors of Chagas disease in Brazil and Mexico: the Virtual Vector Lab
title Automated identification of insect vectors of Chagas disease in Brazil and Mexico: the Virtual Vector Lab
title_full Automated identification of insect vectors of Chagas disease in Brazil and Mexico: the Virtual Vector Lab
title_fullStr Automated identification of insect vectors of Chagas disease in Brazil and Mexico: the Virtual Vector Lab
title_full_unstemmed Automated identification of insect vectors of Chagas disease in Brazil and Mexico: the Virtual Vector Lab
title_short Automated identification of insect vectors of Chagas disease in Brazil and Mexico: the Virtual Vector Lab
title_sort automated identification of insect vectors of chagas disease in brazil and mexico: the virtual vector lab
topic Entomology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5398287/
https://www.ncbi.nlm.nih.gov/pubmed/28439451
http://dx.doi.org/10.7717/peerj.3040
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