A novel set of algorithms to recognize galleries of ambrosia beetle in computerized axial tomography of trees trunks

Autores
Dolinko, Andrés Ezequiel; Costales, Yasmil; Carmaran, Cecilia Cristina; Ceriani Nakamurakare, Esteban Daniel
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Megaplatypus mutatus is an ambrosia beetle that attacks several species of trees by making galleries in the trunks where its larvae and associated fungi develop. This damage spoils the wood for commercial use and cause stem breakage in front of strong winds. Due to the insect´s cryptic lifestyle, gallery analyses have usually been studied by destructive methods. However, they alter the homeostasis of the insect-fungi interaction, modifies the topology of the gallery and, more importantly, does not reveal the 100% complex structure made by the insect. Therefore, a novel way to study this structure is by imaging the galleries by means of computerized axial tomography (CT). This method allows obtaining a three-dimensional representation of the gallery and the pupal chambers to be studied, while the wood and insect sample is not disturbed and generates a high amount of data. The isolation of the galleries and pupal chambers from the CT background images is not simple, because there is not enough contrast between the grey levels of the galleries and the marks generated by internal components of the trunk itself. In this paper, we present a robust algorithm that allows automating the isolation of the galleries and pupal chambers from CT trunk images which can be used in a broad spectrum of image analysis.
Fil: Dolinko, Andrés Ezequiel. Universidad de Buenos Aires. Facultad de Cs.exactas y Naturales. Departamento de Biodiversidad y Biología Experimental. Laboratorio de Micologia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Micología y Botánica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Micología y Botánica; Argentina
Fil: Costales, Yasmil. Universidad Favaloro; Argentina
Fil: Carmaran, Cecilia Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Micología y Botánica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Micología y Botánica; Argentina. Universidad de Buenos Aires. Facultad de Cs.exactas y Naturales. Departamento de Biodiversidad y Biología Experimental. Laboratorio de Micologia; Argentina
Fil: Ceriani Nakamurakare, Esteban Daniel. Universidad de Buenos Aires. Facultad de Cs.exactas y Naturales. Departamento de Biodiversidad y Biología Experimental. Laboratorio de Micologia; Argentina. Universidad Nacional de Luján. Departamento de Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
Tomography
Image recognition
Image processing
Ambrosia beetle
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/publicdomain/zero/1.0/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/215835

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spelling A novel set of algorithms to recognize galleries of ambrosia beetle in computerized axial tomography of trees trunksDolinko, Andrés EzequielCostales, YasmilCarmaran, Cecilia CristinaCeriani Nakamurakare, Esteban DanielTomographyImage recognitionImage processingAmbrosia beetlehttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Megaplatypus mutatus is an ambrosia beetle that attacks several species of trees by making galleries in the trunks where its larvae and associated fungi develop. This damage spoils the wood for commercial use and cause stem breakage in front of strong winds. Due to the insect´s cryptic lifestyle, gallery analyses have usually been studied by destructive methods. However, they alter the homeostasis of the insect-fungi interaction, modifies the topology of the gallery and, more importantly, does not reveal the 100% complex structure made by the insect. Therefore, a novel way to study this structure is by imaging the galleries by means of computerized axial tomography (CT). This method allows obtaining a three-dimensional representation of the gallery and the pupal chambers to be studied, while the wood and insect sample is not disturbed and generates a high amount of data. The isolation of the galleries and pupal chambers from the CT background images is not simple, because there is not enough contrast between the grey levels of the galleries and the marks generated by internal components of the trunk itself. In this paper, we present a robust algorithm that allows automating the isolation of the galleries and pupal chambers from CT trunk images which can be used in a broad spectrum of image analysis.Fil: Dolinko, Andrés Ezequiel. Universidad de Buenos Aires. Facultad de Cs.exactas y Naturales. Departamento de Biodiversidad y Biología Experimental. Laboratorio de Micologia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Micología y Botánica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Micología y Botánica; ArgentinaFil: Costales, Yasmil. Universidad Favaloro; ArgentinaFil: Carmaran, Cecilia Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Micología y Botánica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Micología y Botánica; Argentina. Universidad de Buenos Aires. Facultad de Cs.exactas y Naturales. Departamento de Biodiversidad y Biología Experimental. Laboratorio de Micologia; ArgentinaFil: Ceriani Nakamurakare, Esteban Daniel. Universidad de Buenos Aires. Facultad de Cs.exactas y Naturales. Departamento de Biodiversidad y Biología Experimental. Laboratorio de Micologia; Argentina. Universidad Nacional de Luján. Departamento de Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaCornell University2022-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/215835Dolinko, Andrés Ezequiel; Costales, Yasmil; Carmaran, Cecilia Cristina; Ceriani Nakamurakare, Esteban Daniel; A novel set of algorithms to recognize galleries of ambrosia beetle in computerized axial tomography of trees trunks; Cornell University; Arxiv; 2206; 748; 6-2022; 1-142331-8422CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/arxiv/https://arxiv.org/abs/2206.12748info:eu-repo/semantics/altIdentifier/doi/10.48550/arXiv.2206.12748info:eu-repo/semantics/openAccesshttps://creativecommons.org/publicdomain/zero/1.0/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:11:39Zoai:ri.conicet.gov.ar:11336/215835instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:11:40.166CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A novel set of algorithms to recognize galleries of ambrosia beetle in computerized axial tomography of trees trunks
title A novel set of algorithms to recognize galleries of ambrosia beetle in computerized axial tomography of trees trunks
spellingShingle A novel set of algorithms to recognize galleries of ambrosia beetle in computerized axial tomography of trees trunks
Dolinko, Andrés Ezequiel
Tomography
Image recognition
Image processing
Ambrosia beetle
title_short A novel set of algorithms to recognize galleries of ambrosia beetle in computerized axial tomography of trees trunks
title_full A novel set of algorithms to recognize galleries of ambrosia beetle in computerized axial tomography of trees trunks
title_fullStr A novel set of algorithms to recognize galleries of ambrosia beetle in computerized axial tomography of trees trunks
title_full_unstemmed A novel set of algorithms to recognize galleries of ambrosia beetle in computerized axial tomography of trees trunks
title_sort A novel set of algorithms to recognize galleries of ambrosia beetle in computerized axial tomography of trees trunks
dc.creator.none.fl_str_mv Dolinko, Andrés Ezequiel
Costales, Yasmil
Carmaran, Cecilia Cristina
Ceriani Nakamurakare, Esteban Daniel
author Dolinko, Andrés Ezequiel
author_facet Dolinko, Andrés Ezequiel
Costales, Yasmil
Carmaran, Cecilia Cristina
Ceriani Nakamurakare, Esteban Daniel
author_role author
author2 Costales, Yasmil
Carmaran, Cecilia Cristina
Ceriani Nakamurakare, Esteban Daniel
author2_role author
author
author
dc.subject.none.fl_str_mv Tomography
Image recognition
Image processing
Ambrosia beetle
topic Tomography
Image recognition
Image processing
Ambrosia beetle
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Megaplatypus mutatus is an ambrosia beetle that attacks several species of trees by making galleries in the trunks where its larvae and associated fungi develop. This damage spoils the wood for commercial use and cause stem breakage in front of strong winds. Due to the insect´s cryptic lifestyle, gallery analyses have usually been studied by destructive methods. However, they alter the homeostasis of the insect-fungi interaction, modifies the topology of the gallery and, more importantly, does not reveal the 100% complex structure made by the insect. Therefore, a novel way to study this structure is by imaging the galleries by means of computerized axial tomography (CT). This method allows obtaining a three-dimensional representation of the gallery and the pupal chambers to be studied, while the wood and insect sample is not disturbed and generates a high amount of data. The isolation of the galleries and pupal chambers from the CT background images is not simple, because there is not enough contrast between the grey levels of the galleries and the marks generated by internal components of the trunk itself. In this paper, we present a robust algorithm that allows automating the isolation of the galleries and pupal chambers from CT trunk images which can be used in a broad spectrum of image analysis.
Fil: Dolinko, Andrés Ezequiel. Universidad de Buenos Aires. Facultad de Cs.exactas y Naturales. Departamento de Biodiversidad y Biología Experimental. Laboratorio de Micologia; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Micología y Botánica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Micología y Botánica; Argentina
Fil: Costales, Yasmil. Universidad Favaloro; Argentina
Fil: Carmaran, Cecilia Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Micología y Botánica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Micología y Botánica; Argentina. Universidad de Buenos Aires. Facultad de Cs.exactas y Naturales. Departamento de Biodiversidad y Biología Experimental. Laboratorio de Micologia; Argentina
Fil: Ceriani Nakamurakare, Esteban Daniel. Universidad de Buenos Aires. Facultad de Cs.exactas y Naturales. Departamento de Biodiversidad y Biología Experimental. Laboratorio de Micologia; Argentina. Universidad Nacional de Luján. Departamento de Tecnología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description Megaplatypus mutatus is an ambrosia beetle that attacks several species of trees by making galleries in the trunks where its larvae and associated fungi develop. This damage spoils the wood for commercial use and cause stem breakage in front of strong winds. Due to the insect´s cryptic lifestyle, gallery analyses have usually been studied by destructive methods. However, they alter the homeostasis of the insect-fungi interaction, modifies the topology of the gallery and, more importantly, does not reveal the 100% complex structure made by the insect. Therefore, a novel way to study this structure is by imaging the galleries by means of computerized axial tomography (CT). This method allows obtaining a three-dimensional representation of the gallery and the pupal chambers to be studied, while the wood and insect sample is not disturbed and generates a high amount of data. The isolation of the galleries and pupal chambers from the CT background images is not simple, because there is not enough contrast between the grey levels of the galleries and the marks generated by internal components of the trunk itself. In this paper, we present a robust algorithm that allows automating the isolation of the galleries and pupal chambers from CT trunk images which can be used in a broad spectrum of image analysis.
publishDate 2022
dc.date.none.fl_str_mv 2022-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/215835
Dolinko, Andrés Ezequiel; Costales, Yasmil; Carmaran, Cecilia Cristina; Ceriani Nakamurakare, Esteban Daniel; A novel set of algorithms to recognize galleries of ambrosia beetle in computerized axial tomography of trees trunks; Cornell University; Arxiv; 2206; 748; 6-2022; 1-14
2331-8422
CONICET Digital
CONICET
url http://hdl.handle.net/11336/215835
identifier_str_mv Dolinko, Andrés Ezequiel; Costales, Yasmil; Carmaran, Cecilia Cristina; Ceriani Nakamurakare, Esteban Daniel; A novel set of algorithms to recognize galleries of ambrosia beetle in computerized axial tomography of trees trunks; Cornell University; Arxiv; 2206; 748; 6-2022; 1-14
2331-8422
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/arxiv/https://arxiv.org/abs/2206.12748
info:eu-repo/semantics/altIdentifier/doi/10.48550/arXiv.2206.12748
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/publicdomain/zero/1.0/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/publicdomain/zero/1.0/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Cornell University
publisher.none.fl_str_mv Cornell University
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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