Super-resolved edge detection in optical microscopy images by superposition of virtual point sources

Autores
Brinatti Vazquez, Guillermo Daniel; Martínez, Oscar E.; Martinez, Sandra Rita
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
A new approach to the edge detection problem is presented which is specially designed to achieve high accuracy detection, below instrumental resolution (super resolution) in microscopy images. The method is based in a modified version of a recently published algorithm known as SUPPOSe, which performs a numerical reconstruction of an image as a superposition of virtual point sources. The method was tested in simulated and experimental optical microscopy images and compared to the standard Laplacian of Gaussian algorithm, showing huge differences when the size of the object is smaller than the lateral resolution provided by the instrument.
Fil: Brinatti Vazquez, Guillermo Daniel. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Martínez, Oscar E.. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Martinez, Sandra Rita. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; Argentina
Materia
Superresolution
Edge-Detection
Deconvolution
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/143891
Acceder
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Super-resolved edge detection in optical microscopy images by superposition of virtual point sourcesBrinatti Vazquez, Guillermo DanielMartínez, Oscar E.Martinez, Sandra RitaSuperresolutionEdge-DetectionDeconvolutionhttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1A new approach to the edge detection problem is presented which is specially designed to achieve high accuracy detection, below instrumental resolution (super resolution) in microscopy images. The method is based in a modified version of a recently published algorithm known as SUPPOSe, which performs a numerical reconstruction of an image as a superposition of virtual point sources. The method was tested in simulated and experimental optical microscopy images and compared to the standard Laplacian of Gaussian algorithm, showing huge differences when the size of the object is smaller than the lateral resolution provided by the instrument.Fil: Brinatti Vazquez, Guillermo Daniel. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Martínez, Oscar E.. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Martinez, Sandra Rita. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; ArgentinaOptical Society of America2020-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/143891Brinatti Vazquez, Guillermo Daniel; Martínez, Oscar E.; Martinez, Sandra Rita; Super-resolved edge detection in optical microscopy images by superposition of virtual point sources; Optical Society of America; Optics Express; 28; 17; 8-2020; 25319-253341094-4087CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1364/OE.397125info:eu-repo/semantics/altIdentifier/url/https://www.osapublishing.org/oe/fulltext.cfm?uri=oe-28-17-25319&id=434388info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-17T11:31:31Zoai:ri.conicet.gov.ar:11336/143891instacron: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:34982025-09-17 11:31:32.167CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Super-resolved edge detection in optical microscopy images by superposition of virtual point sources
title Super-resolved edge detection in optical microscopy images by superposition of virtual point sources
spellingShingle Super-resolved edge detection in optical microscopy images by superposition of virtual point sources
Brinatti Vazquez, Guillermo Daniel
Superresolution
Edge-Detection
Deconvolution
title_short Super-resolved edge detection in optical microscopy images by superposition of virtual point sources
title_full Super-resolved edge detection in optical microscopy images by superposition of virtual point sources
title_fullStr Super-resolved edge detection in optical microscopy images by superposition of virtual point sources
title_full_unstemmed Super-resolved edge detection in optical microscopy images by superposition of virtual point sources
title_sort Super-resolved edge detection in optical microscopy images by superposition of virtual point sources
dc.creator.none.fl_str_mv Brinatti Vazquez, Guillermo Daniel
Martínez, Oscar E.
Martinez, Sandra Rita
author Brinatti Vazquez, Guillermo Daniel
author_facet Brinatti Vazquez, Guillermo Daniel
Martínez, Oscar E.
Martinez, Sandra Rita
author_role author
author2 Martínez, Oscar E.
Martinez, Sandra Rita
author2_role author
author
dc.subject.none.fl_str_mv Superresolution
Edge-Detection
Deconvolution
topic Superresolution
Edge-Detection
Deconvolution
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv A new approach to the edge detection problem is presented which is specially designed to achieve high accuracy detection, below instrumental resolution (super resolution) in microscopy images. The method is based in a modified version of a recently published algorithm known as SUPPOSe, which performs a numerical reconstruction of an image as a superposition of virtual point sources. The method was tested in simulated and experimental optical microscopy images and compared to the standard Laplacian of Gaussian algorithm, showing huge differences when the size of the object is smaller than the lateral resolution provided by the instrument.
Fil: Brinatti Vazquez, Guillermo Daniel. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Martínez, Oscar E.. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Martinez, Sandra Rita. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Investigaciones Matemáticas "Luis A. Santaló". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Investigaciones Matemáticas "Luis A. Santaló"; Argentina
description A new approach to the edge detection problem is presented which is specially designed to achieve high accuracy detection, below instrumental resolution (super resolution) in microscopy images. The method is based in a modified version of a recently published algorithm known as SUPPOSe, which performs a numerical reconstruction of an image as a superposition of virtual point sources. The method was tested in simulated and experimental optical microscopy images and compared to the standard Laplacian of Gaussian algorithm, showing huge differences when the size of the object is smaller than the lateral resolution provided by the instrument.
publishDate 2020
dc.date.none.fl_str_mv 2020-08
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/11336/143891
Brinatti Vazquez, Guillermo Daniel; Martínez, Oscar E.; Martinez, Sandra Rita; Super-resolved edge detection in optical microscopy images by superposition of virtual point sources; Optical Society of America; Optics Express; 28; 17; 8-2020; 25319-25334
1094-4087
CONICET Digital
CONICET
url http://hdl.handle.net/11336/143891
identifier_str_mv Brinatti Vazquez, Guillermo Daniel; Martínez, Oscar E.; Martinez, Sandra Rita; Super-resolved edge detection in optical microscopy images by superposition of virtual point sources; Optical Society of America; Optics Express; 28; 17; 8-2020; 25319-25334
1094-4087
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1364/OE.397125
info:eu-repo/semantics/altIdentifier/url/https://www.osapublishing.org/oe/fulltext.cfm?uri=oe-28-17-25319&id=434388
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Optical Society of America
publisher.none.fl_str_mv Optical Society of America
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
_version_ 1843606673724276736
score 13.001348

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