Manual and automatic image analysis segmentation methods for blood flow studies in microchannels
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10198/24780 |
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 analysed 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 know microfluidic phenomena cell-free layer thickness, two developed methods are present and discuss in order to demonstrate their feasibility for accurate data acquisition in such studies Additionally, a comparison analysis between manual and automatic methods was performed. |
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Manual and automatic image analysis segmentation methods for blood flow studies in microchannelsBlood flowParticle trackingRed blood cellsManual methodsAutomatic methodsImage analysisBiomicrofluidicsIn 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 analysed 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 know microfluidic phenomena cell-free layer thickness, two developed methods are present and discuss in order to demonstrate their feasibility for 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.Biblioteca Digital do IPBCarvalho, Violeta MenesesGonçalves, Inês M.Souza, Andrews Victor AlmeidaSouza, Maria SabrinaBento, DavidRibeiro, J.E.Lima, Rui A.Pinho, Diana2022-01-20T10:32:12Z20212021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10198/24780engCarvalho, Violeta; Gonçalves, Inês M.; Souza, Andrews; Souza, Maria S.; Bento, David; Ribeiro, J.E.; Lima, Rui; Pinho, Diana (2021). Manual and automatic image analysis segmentation methods for blood flow studies in microchannels. Micromachines. ISSN 2072-666X. 12:3, p. 1-202072-666X10.3390/mi12030317info: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:RCAAP2023-11-21T10:55:41Zoai:bibliotecadigital.ipb.pt:10198/24780Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:15:39.443184Repositório 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 |
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 Bento, David Ribeiro, J.E. Lima, Rui A. Pinho, Diana |
author_role |
author |
author2 |
Gonçalves, Inês M. Souza, Andrews Victor Almeida Souza, Maria Sabrina Bento, David Ribeiro, J.E. Lima, Rui A. Pinho, Diana |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
Biblioteca Digital do IPB |
dc.contributor.author.fl_str_mv |
Carvalho, Violeta Meneses Gonçalves, Inês M. Souza, Andrews Victor Almeida Souza, Maria Sabrina Bento, David Ribeiro, J.E. Lima, Rui A. Pinho, Diana |
dc.subject.por.fl_str_mv |
Blood flow Particle tracking Red blood cells Manual methods Automatic methods Image analysis Biomicrofluidics |
topic |
Blood flow Particle tracking Red blood cells Manual methods Automatic methods Image analysis Biomicrofluidics |
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 analysed 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 know microfluidic phenomena cell-free layer thickness, two developed methods are present and discuss in order to demonstrate their feasibility for 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 2021-01-01T00:00:00Z 2022-01-20T10:32:12Z |
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/10198/24780 |
url |
http://hdl.handle.net/10198/24780 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Carvalho, Violeta; Gonçalves, Inês M.; Souza, Andrews; Souza, Maria S.; Bento, David; Ribeiro, J.E.; Lima, Rui; Pinho, Diana (2021). Manual and automatic image analysis segmentation methods for blood flow studies in microchannels. Micromachines. ISSN 2072-666X. 12:3, p. 1-20 2072-666X 10.3390/mi12030317 |
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.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 |
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