Manual and automatic image analysis segmentation methods for blood flow studies in microchannels

Detalhes bibliográficos
Autor(a) principal: Carvalho, Violeta Meneses
Data de Publicação: 2021
Outros Autores: Gonçalves, Inês M., Souza, Andrews Victor Almeida, Souza, Maria Sabrina Veira Miranda Palva, Bento, David, Ribeiro, João E., Lima, Rui Alberto Madeira Macedo, Pinho, Diana
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/1822/72660
Resumo: In blood flow studies, image analysis plays an extremely important role to examine raw data obtained by high-speed video microscopy systems. This work shows different ways to process the images which contain various blood phenomena happening in microfluidic devices and in microcirculation. For this purpose, the current methods used for tracking red blood cells (RBCs) flowing through a glass capillary and techniques to measure the cell-free layer thickness in different kinds of microchannels will be presented. Most of the past blood flow experimental data have been collected and analyzed by means of manual methods, that can be extremely reliable, but they are highly time-consuming, user-intensive, repetitive, and the results can be subjective to user-induced errors. For this reason, it is crucial to develop image analysis methods able to obtain the data automatically. Concerning automatic image analysis methods for individual RBCs tracking and to measure the well known microfluidic phenomena cell-free layer, two developed methods are presented and discussed in order to demonstrate their feasibility to obtain accurate data acquisition in such studies. Additionally, a comparison analysis between manual and automatic methods was performed.
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spelling Manual and automatic image analysis segmentation methods for blood flow studies in microchannelsBlood flowParticle trackingRed blood cellsManual methodsAutomatic methodsImage analysisBiomicrofluidicsScience & TechnologyIn blood flow studies, image analysis plays an extremely important role to examine raw data obtained by high-speed video microscopy systems. This work shows different ways to process the images which contain various blood phenomena happening in microfluidic devices and in microcirculation. For this purpose, the current methods used for tracking red blood cells (RBCs) flowing through a glass capillary and techniques to measure the cell-free layer thickness in different kinds of microchannels will be presented. Most of the past blood flow experimental data have been collected and analyzed by means of manual methods, that can be extremely reliable, but they are highly time-consuming, user-intensive, repetitive, and the results can be subjective to user-induced errors. For this reason, it is crucial to develop image analysis methods able to obtain the data automatically. Concerning automatic image analysis methods for individual RBCs tracking and to measure the well known microfluidic phenomena cell-free layer, two developed methods are presented and discussed in order to demonstrate their feasibility to obtain accurate data acquisition in such studies. Additionally, a comparison analysis between manual and automatic methods was performed.This project has been funded by Portuguese national funds of FCT/MCTES (PIDDAC) through the base funding from the following research units: UIDB/00532/2020 (Transport Phenomena Research Center—CEFT), UIDB/04077/2020 (Mechanical Engineering and Resource Sustainability Center—MEtRICs), UIDB/00690/2020 (CIMO). The authors are also grateful for the partial funding of FCT through the projects, NORTE-01-0145-FEDER-029394 (PTDC/EMD-EMD/29394/2017) and NORTE-01-0145-FEDER-030171 (PTDC/EMD-EMD/30171/2017) funded by COMPETE2020, NORTE2020, PORTUGAL2020 and FEDER. D. Bento acknowledges the PhD scholarship SFRH/BD/ 91192/2012 granted by FCT.Multidisciplinary Digital Publishing Institute (MDPI)Universidade do MinhoCarvalho, Violeta MenesesGonçalves, Inês M.Souza, Andrews Victor AlmeidaSouza, Maria Sabrina Veira Miranda PalvaBento, DavidRibeiro, João E.Lima, Rui Alberto Madeira MacedoPinho, Diana2021-03-182021-03-18T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/72660engCarvalho, V.; Gonçalves, I.M.; Souza, A.; Souza, M.S.; Bento, D.; Ribeiro, J.E.; Lima, R.; Pinho, D. Manual and Automatic Image Analysis Segmentation Methods for Blood Flow Studies in Microchannels. Micromachines 2021, 12, 317. https://doi.org/10.3390/mi120303172072-666X10.3390/mi12030317https://www.mdpi.com/2072-666X/12/3/317info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:01:38Zoai:repositorium.sdum.uminho.pt:1822/72660Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:51:33.638827Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Manual and automatic image analysis segmentation methods for blood flow studies in microchannels
title Manual and automatic image analysis segmentation methods for blood flow studies in microchannels
spellingShingle Manual and automatic image analysis segmentation methods for blood flow studies in microchannels
Carvalho, Violeta Meneses
Blood flow
Particle tracking
Red blood cells
Manual methods
Automatic methods
Image analysis
Biomicrofluidics
Science & Technology
title_short Manual and automatic image analysis segmentation methods for blood flow studies in microchannels
title_full Manual and automatic image analysis segmentation methods for blood flow studies in microchannels
title_fullStr Manual and automatic image analysis segmentation methods for blood flow studies in microchannels
title_full_unstemmed Manual and automatic image analysis segmentation methods for blood flow studies in microchannels
title_sort Manual and automatic image analysis segmentation methods for blood flow studies in microchannels
author Carvalho, Violeta Meneses
author_facet Carvalho, Violeta Meneses
Gonçalves, Inês M.
Souza, Andrews Victor Almeida
Souza, Maria Sabrina Veira Miranda Palva
Bento, David
Ribeiro, João E.
Lima, Rui Alberto Madeira Macedo
Pinho, Diana
author_role author
author2 Gonçalves, Inês M.
Souza, Andrews Victor Almeida
Souza, Maria Sabrina Veira Miranda Palva
Bento, David
Ribeiro, João E.
Lima, Rui Alberto Madeira Macedo
Pinho, Diana
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Carvalho, Violeta Meneses
Gonçalves, Inês M.
Souza, Andrews Victor Almeida
Souza, Maria Sabrina Veira Miranda Palva
Bento, David
Ribeiro, João E.
Lima, Rui Alberto Madeira Macedo
Pinho, Diana
dc.subject.por.fl_str_mv Blood flow
Particle tracking
Red blood cells
Manual methods
Automatic methods
Image analysis
Biomicrofluidics
Science & Technology
topic Blood flow
Particle tracking
Red blood cells
Manual methods
Automatic methods
Image analysis
Biomicrofluidics
Science & Technology
description In blood flow studies, image analysis plays an extremely important role to examine raw data obtained by high-speed video microscopy systems. This work shows different ways to process the images which contain various blood phenomena happening in microfluidic devices and in microcirculation. For this purpose, the current methods used for tracking red blood cells (RBCs) flowing through a glass capillary and techniques to measure the cell-free layer thickness in different kinds of microchannels will be presented. Most of the past blood flow experimental data have been collected and analyzed by means of manual methods, that can be extremely reliable, but they are highly time-consuming, user-intensive, repetitive, and the results can be subjective to user-induced errors. For this reason, it is crucial to develop image analysis methods able to obtain the data automatically. Concerning automatic image analysis methods for individual RBCs tracking and to measure the well known microfluidic phenomena cell-free layer, two developed methods are presented and discussed in order to demonstrate their feasibility to obtain accurate data acquisition in such studies. Additionally, a comparison analysis between manual and automatic methods was performed.
publishDate 2021
dc.date.none.fl_str_mv 2021-03-18
2021-03-18T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/72660
url http://hdl.handle.net/1822/72660
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Carvalho, V.; Gonçalves, I.M.; Souza, A.; Souza, M.S.; Bento, D.; Ribeiro, J.E.; Lima, R.; Pinho, D. Manual and Automatic Image Analysis Segmentation Methods for Blood Flow Studies in Microchannels. Micromachines 2021, 12, 317. https://doi.org/10.3390/mi12030317
2072-666X
10.3390/mi12030317
https://www.mdpi.com/2072-666X/12/3/317
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute (MDPI)
publisher.none.fl_str_mv Multidisciplinary Digital Publishing Institute (MDPI)
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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