Cell quantification in digital contrast microscopy images with convolutional neural networks algorithm
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Institucional da FIOCRUZ (ARCA) |
Texto Completo: | https://www.arca.fiocruz.br/handle/icict/57703 https://doi.org/10.1038/s41598-023-29694-7 |
Resumo: | Fundação Oswaldo Cruz. Instituto Carlos Chagas. Curitiba, PR, Brasil. |
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Ferreira, E. K. G. D.Lara, D. S. D.Silveira, Guilherme Ferreira2023-04-06T18:11:43Z2023-04-06T18:11:43Z2023FEREIRA, E. K. G. D. et al. Cell quantification in digital contrast microscopy images with convolutional neural networks algorithm. Scientific Reports, v. 13, n. 2596, p. 1–11, 2023.2045-2322https://www.arca.fiocruz.br/handle/icict/57703https://doi.org/10.1038/s41598-023-29694-7porNature ResearchCell quantification in digital contrast microscopy images with convolutional neural networks algorithminfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleFundação Oswaldo Cruz. Instituto Carlos Chagas. Curitiba, PR, Brasil.Universidade Federal de Minas Gerais. Departamento de Engenharia Elétrica. Belo Horizonte, MG, Brasil.Fundação Oswaldo Cruz. Instituto Carlos Chagas. Curitiba, PR, Brasil.High Content Screening (HCS) combines high throughput techniques with the ability to generate cellular images of biological systems. The objective of this work is to evaluate the performance of predictive models using CNN to identify the number of cells present in digital contrast microscopy images obtained by HCS. One way to evaluate the algorithm was through the Mean Squared Error metric. The MSE was 4,335.99 in the A549 cell line, 25,295.23 in the Huh7 and 36,897.03 in the 3T3. After obtaining these values, different parameters of the models were changed to verify how they behave. By reducing the number of images, the MSE increased considerably, with the A549 cell line changing to 49,973.52, Huh7 to 79,473.88 and 3T3 to 52,977.05. Correlation analyzes were performed for the diferent models. In lineage A549, the best model showed a positive correlation with R= 0.953. In Huh7, the best correlation of the model was R= 0.821, it was also a positive correlation. In 3T3, the models showed no correlation, with the best model having R= 0.100. The models performed well in quantifying the number of cells, and the number and quality of the images interfered with this predictive ability.Microscopy, ElectronModels, BiologicalMicroscopia EletrônicaModelos Biológicosinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da FIOCRUZ (ARCA)instname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZLICENSElicense.txtlicense.txttext/plain; charset=utf-82991https://www.arca.fiocruz.br/bitstream/icict/57703/1/license.txt5a560609d32a3863062d77ff32785d58MD51ORIGINAL41598_2023_Article_29694.pdf41598_2023_Article_29694.pdfapplication/pdf2708076https://www.arca.fiocruz.br/bitstream/icict/57703/2/41598_2023_Article_29694.pdf44ae6b596088d8ce617c10f27976547bMD52icict/577032023-04-06 15:11:45.058oai:www.arca.fiocruz.br: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ório InstitucionalPUBhttps://www.arca.fiocruz.br/oai/requestrepositorio.arca@fiocruz.bropendoar:21352023-04-06T18:11:45Repositório Institucional da FIOCRUZ (ARCA) - Fundação Oswaldo Cruz (FIOCRUZ)false |
dc.title.en_US.fl_str_mv |
Cell quantification in digital contrast microscopy images with convolutional neural networks algorithm |
title |
Cell quantification in digital contrast microscopy images with convolutional neural networks algorithm |
spellingShingle |
Cell quantification in digital contrast microscopy images with convolutional neural networks algorithm Ferreira, E. K. G. D. Microscopy, Electron Models, Biological Microscopia Eletrônica Modelos Biológicos |
title_short |
Cell quantification in digital contrast microscopy images with convolutional neural networks algorithm |
title_full |
Cell quantification in digital contrast microscopy images with convolutional neural networks algorithm |
title_fullStr |
Cell quantification in digital contrast microscopy images with convolutional neural networks algorithm |
title_full_unstemmed |
Cell quantification in digital contrast microscopy images with convolutional neural networks algorithm |
title_sort |
Cell quantification in digital contrast microscopy images with convolutional neural networks algorithm |
author |
Ferreira, E. K. G. D. |
author_facet |
Ferreira, E. K. G. D. Lara, D. S. D. Silveira, Guilherme Ferreira |
author_role |
author |
author2 |
Lara, D. S. D. Silveira, Guilherme Ferreira |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Ferreira, E. K. G. D. Lara, D. S. D. Silveira, Guilherme Ferreira |
dc.subject.en.en_US.fl_str_mv |
Microscopy, Electron Models, Biological |
topic |
Microscopy, Electron Models, Biological Microscopia Eletrônica Modelos Biológicos |
dc.subject.decs.en_US.fl_str_mv |
Microscopia Eletrônica Modelos Biológicos |
description |
Fundação Oswaldo Cruz. Instituto Carlos Chagas. Curitiba, PR, Brasil. |
publishDate |
2023 |
dc.date.accessioned.fl_str_mv |
2023-04-06T18:11:43Z |
dc.date.available.fl_str_mv |
2023-04-06T18:11:43Z |
dc.date.issued.fl_str_mv |
2023 |
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.citation.fl_str_mv |
FEREIRA, E. K. G. D. et al. Cell quantification in digital contrast microscopy images with convolutional neural networks algorithm. Scientific Reports, v. 13, n. 2596, p. 1–11, 2023. |
dc.identifier.uri.fl_str_mv |
https://www.arca.fiocruz.br/handle/icict/57703 |
dc.identifier.issn.en_US.fl_str_mv |
2045-2322 |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1038/s41598-023-29694-7 |
identifier_str_mv |
FEREIRA, E. K. G. D. et al. Cell quantification in digital contrast microscopy images with convolutional neural networks algorithm. Scientific Reports, v. 13, n. 2596, p. 1–11, 2023. 2045-2322 |
url |
https://www.arca.fiocruz.br/handle/icict/57703 https://doi.org/10.1038/s41598-023-29694-7 |
dc.language.iso.fl_str_mv |
por |
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por |
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info:eu-repo/semantics/openAccess |
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openAccess |
dc.publisher.none.fl_str_mv |
Nature Research |
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Nature Research |
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reponame:Repositório Institucional da FIOCRUZ (ARCA) instname:Fundação Oswaldo Cruz (FIOCRUZ) instacron:FIOCRUZ |
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Fundação Oswaldo Cruz (FIOCRUZ) |
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FIOCRUZ |
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FIOCRUZ |
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Repositório Institucional da FIOCRUZ (ARCA) |
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Repositório Institucional da FIOCRUZ (ARCA) |
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https://www.arca.fiocruz.br/bitstream/icict/57703/1/license.txt https://www.arca.fiocruz.br/bitstream/icict/57703/2/41598_2023_Article_29694.pdf |
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