Discrete SUPPOSe : A new, faster and accurate superresolution method for applications to fluorescence microscopy images

Autores
Martinez, Sandra Rita; Martinez, Oscar Eduardo
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In this article we define Discrete SUPPOSe, a new and faster version of the single shot super resolution SUPPOSe (Superposition of virtual point sources) method. The SUPPOSe method for super-resolution of fluorescent microscope images relies in assuming that the sample source distribution can be modeled as a superposition of virtual point sources of equal intensities distributed in a continuous space, converting the ill posed deconvolution problem into a well posed one. In this work we present a faster new method that consists on discretizing the continuum problem, using a normalized covariance instead of a for the fitting function and hence transforming the convolution (the main computational time) into a multiplication, and modifying the mutation step of the genetic algorithm. We compare precision, accuracy, resolution and computation time. It is also shown that despite the spatial discretization in Discrete SUPPOSe similar figures for precision, accuracy and resolution are obtained. The algorithm was implemented in Matlab running on a CPU obtaining with a speed improvement factor of more than 15 for one image of 48 × 48 pixels. Processing images in parallel in a 16 cores CPU a 1Mpixel image is computed 240 times faster than the standard SUPPOSe in a 2600 core GPU. Experimental images were used to validate the method.
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
Fil: Martinez, Oscar Eduardo. Universidad de Buenos Aires. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
IMAGE
RESOLUTION
SUPER-RESOLUTION
OPTIMIZATION
MICROSCOPY
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/255186
Acceder
id CONICETDig_32a0f1fe70b7755e35946fd4f931564d
oai_identifier_str oai:ri.conicet.gov.ar:11336/255186
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Discrete SUPPOSe : A new, faster and accurate superresolution method for applications to fluorescence microscopy imagesMartinez, Sandra RitaMartinez, Oscar EduardoIMAGERESOLUTIONSUPER-RESOLUTIONOPTIMIZATIONMICROSCOPYhttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1In this article we define Discrete SUPPOSe, a new and faster version of the single shot super resolution SUPPOSe (Superposition of virtual point sources) method. The SUPPOSe method for super-resolution of fluorescent microscope images relies in assuming that the sample source distribution can be modeled as a superposition of virtual point sources of equal intensities distributed in a continuous space, converting the ill posed deconvolution problem into a well posed one. In this work we present a faster new method that consists on discretizing the continuum problem, using a normalized covariance instead of a for the fitting function and hence transforming the convolution (the main computational time) into a multiplication, and modifying the mutation step of the genetic algorithm. We compare precision, accuracy, resolution and computation time. It is also shown that despite the spatial discretization in Discrete SUPPOSe similar figures for precision, accuracy and resolution are obtained. The algorithm was implemented in Matlab running on a CPU obtaining with a speed improvement factor of more than 15 for one image of 48 × 48 pixels. Processing images in parallel in a 16 cores CPU a 1Mpixel image is computed 240 times faster than the standard SUPPOSe in a 2600 core GPU. Experimental images were used to validate the method.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"; ArgentinaFil: Martinez, Oscar Eduardo. Universidad de Buenos Aires. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaElsevier2024-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/255186Martinez, Sandra Rita; Martinez, Oscar Eduardo; Discrete SUPPOSe : A new, faster and accurate superresolution method for applications to fluorescence microscopy images; Elsevier; Results in Optics; 16; 7-2024; 1-112666-9501CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.rio.2024.100715info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S2666950124001123?via%3Dihubinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:42:57Zoai:ri.conicet.gov.ar:11336/255186instacron: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:34982025-09-29 09:42:57.554CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Discrete SUPPOSe : A new, faster and accurate superresolution method for applications to fluorescence microscopy images
title Discrete SUPPOSe : A new, faster and accurate superresolution method for applications to fluorescence microscopy images
spellingShingle Discrete SUPPOSe : A new, faster and accurate superresolution method for applications to fluorescence microscopy images
Martinez, Sandra Rita
IMAGE
RESOLUTION
SUPER-RESOLUTION
OPTIMIZATION
MICROSCOPY
title_short Discrete SUPPOSe : A new, faster and accurate superresolution method for applications to fluorescence microscopy images
title_full Discrete SUPPOSe : A new, faster and accurate superresolution method for applications to fluorescence microscopy images
title_fullStr Discrete SUPPOSe : A new, faster and accurate superresolution method for applications to fluorescence microscopy images
title_full_unstemmed Discrete SUPPOSe : A new, faster and accurate superresolution method for applications to fluorescence microscopy images
title_sort Discrete SUPPOSe : A new, faster and accurate superresolution method for applications to fluorescence microscopy images
dc.creator.none.fl_str_mv Martinez, Sandra Rita
Martinez, Oscar Eduardo
author Martinez, Sandra Rita
author_facet Martinez, Sandra Rita
Martinez, Oscar Eduardo
author_role author
author2 Martinez, Oscar Eduardo
author2_role author
dc.subject.none.fl_str_mv IMAGE
RESOLUTION
SUPER-RESOLUTION
OPTIMIZATION
MICROSCOPY
topic IMAGE
RESOLUTION
SUPER-RESOLUTION
OPTIMIZATION
MICROSCOPY
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In this article we define Discrete SUPPOSe, a new and faster version of the single shot super resolution SUPPOSe (Superposition of virtual point sources) method. The SUPPOSe method for super-resolution of fluorescent microscope images relies in assuming that the sample source distribution can be modeled as a superposition of virtual point sources of equal intensities distributed in a continuous space, converting the ill posed deconvolution problem into a well posed one. In this work we present a faster new method that consists on discretizing the continuum problem, using a normalized covariance instead of a for the fitting function and hence transforming the convolution (the main computational time) into a multiplication, and modifying the mutation step of the genetic algorithm. We compare precision, accuracy, resolution and computation time. It is also shown that despite the spatial discretization in Discrete SUPPOSe similar figures for precision, accuracy and resolution are obtained. The algorithm was implemented in Matlab running on a CPU obtaining with a speed improvement factor of more than 15 for one image of 48 × 48 pixels. Processing images in parallel in a 16 cores CPU a 1Mpixel image is computed 240 times faster than the standard SUPPOSe in a 2600 core GPU. Experimental images were used to validate the method.
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
Fil: Martinez, Oscar Eduardo. Universidad de Buenos Aires. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description In this article we define Discrete SUPPOSe, a new and faster version of the single shot super resolution SUPPOSe (Superposition of virtual point sources) method. The SUPPOSe method for super-resolution of fluorescent microscope images relies in assuming that the sample source distribution can be modeled as a superposition of virtual point sources of equal intensities distributed in a continuous space, converting the ill posed deconvolution problem into a well posed one. In this work we present a faster new method that consists on discretizing the continuum problem, using a normalized covariance instead of a for the fitting function and hence transforming the convolution (the main computational time) into a multiplication, and modifying the mutation step of the genetic algorithm. We compare precision, accuracy, resolution and computation time. It is also shown that despite the spatial discretization in Discrete SUPPOSe similar figures for precision, accuracy and resolution are obtained. The algorithm was implemented in Matlab running on a CPU obtaining with a speed improvement factor of more than 15 for one image of 48 × 48 pixels. Processing images in parallel in a 16 cores CPU a 1Mpixel image is computed 240 times faster than the standard SUPPOSe in a 2600 core GPU. Experimental images were used to validate the method.
publishDate 2024
dc.date.none.fl_str_mv 2024-07
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/11336/255186
Martinez, Sandra Rita; Martinez, Oscar Eduardo; Discrete SUPPOSe : A new, faster and accurate superresolution method for applications to fluorescence microscopy images; Elsevier; Results in Optics; 16; 7-2024; 1-11
2666-9501
CONICET Digital
CONICET
url http://hdl.handle.net/11336/255186
identifier_str_mv Martinez, Sandra Rita; Martinez, Oscar Eduardo; Discrete SUPPOSe : A new, faster and accurate superresolution method for applications to fluorescence microscopy images; Elsevier; Results in Optics; 16; 7-2024; 1-11
2666-9501
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.rio.2024.100715
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S2666950124001123?via%3Dihub
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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_ 1844613351937671168
score 13.070432

Publicaciones similares