Rastreamento de células em vídeos 3D
Autor(a) principal: | |
---|---|
Data de Publicação: | 2018 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFS |
Texto Completo: | http://ri.ufs.br/jspui/handle/riufs/10782 |
Resumo: | Performing cell tracking is important for curing and preventing diseases. This is due to the fact that cellular motility is linked to several cellular processes. However, performing the analysis of the trajectory of a cell is not a simple job, because to store the information of the trajectory it is necessary a great amount of images, mainly in 3D images. Thus, it is necessary to create algorithms that can perform cell tracking in a practical and automatic way. In this work was given a continuation of the work of conclusion of course (TCC) of Sousa (2015) in order to improve the tracking algorithm already implemented and presented in Sousa (2015). To overcome the shortcomings of the algorithm implemented by Sousa (2015), modifications were made to the segmentation, labeling and tracking phases. In addition, methods have been added for the detection of cell division and the entry and exit of new cells of the video. The validation of the algorithm was done through an evaluation software that has routines for both the segmentation and the tracking part. 11 datasets were used for the validation, and the proposed algorithm was able to obtain results for 7 of them. Among the 7 datasets, 3 were 2D and the other 4, 3D. Although the results were not satisfactory for the 2D datasets, the 3Ds obtained satisfactory results during the tracking phase, with averages of accuracy ranging from 90.1% to 94.4%. From the validation, it was realized that, even having obtained satisfactory values, including some of them better than some found in the state of the art, the algorithm still needs improvements. |
id |
UFS-2_2151ec683840e1af5f14799ee336e38b |
---|---|
oai_identifier_str |
oai:ufs.br:riufs/10782 |
network_acronym_str |
UFS-2 |
network_name_str |
Repositório Institucional da UFS |
repository_id_str |
|
spelling |
Sousa, Davy Oliveira BarrosMacedo, Hendrik Teixeira2019-03-28T23:30:07Z2019-03-28T23:30:07Z2018-08-28SOUSA, Davy Oliveira Barros. Rastreamento de células em vídeos 3D. 2018. 72 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Sergipe, São Cristóvão, SE, 2018.http://ri.ufs.br/jspui/handle/riufs/10782Performing cell tracking is important for curing and preventing diseases. This is due to the fact that cellular motility is linked to several cellular processes. However, performing the analysis of the trajectory of a cell is not a simple job, because to store the information of the trajectory it is necessary a great amount of images, mainly in 3D images. Thus, it is necessary to create algorithms that can perform cell tracking in a practical and automatic way. In this work was given a continuation of the work of conclusion of course (TCC) of Sousa (2015) in order to improve the tracking algorithm already implemented and presented in Sousa (2015). To overcome the shortcomings of the algorithm implemented by Sousa (2015), modifications were made to the segmentation, labeling and tracking phases. In addition, methods have been added for the detection of cell division and the entry and exit of new cells of the video. The validation of the algorithm was done through an evaluation software that has routines for both the segmentation and the tracking part. 11 datasets were used for the validation, and the proposed algorithm was able to obtain results for 7 of them. Among the 7 datasets, 3 were 2D and the other 4, 3D. Although the results were not satisfactory for the 2D datasets, the 3Ds obtained satisfactory results during the tracking phase, with averages of accuracy ranging from 90.1% to 94.4%. From the validation, it was realized that, even having obtained satisfactory values, including some of them better than some found in the state of the art, the algorithm still needs improvements.Realizar o rastreamento de células é importante para a cura e prevenção de doenças. Isso se deve ao fato da motilidade celular estar ligada a vários processos celulares. Porém, realizar a análise da trajetória de uma célula não é um trabalho simples, pois para armazenar as informações da trajetória é necessário uma grande quantidade de imagens, principalmente em imagens 3D. Dessa forma, faz-se necessária a criação de algoritmos que possam realizar o rastreamento celular de forma prática e automática. Neste trabalho foi dada continuidade ao trabalho de conclusão de curso (TCC) de Sousa (2015) de forma a melhorar o algoritmo de rastreamento já implementado e apresentado em Sousa (2015). Para suprir as deficiências do algoritmo implementado por Sousa (2015), foram feitas modificações na fase de segmentação, de rotulação e de rastreamento. Além disso, foram adicionados métodos para a detecção de divisão celular e a entrada e saída de novas células do vídeo. A validação do algoritmo foi feita por meio de um software de avaliação que possui rotinas tanto para a parte de segmentação quanto para a de rastreamento. Foram utilizados 11 datasets para a validação, sendo que o algoritmo proposto conseguiu obter resultados para 7 deles. Dentre os 7 datasets, 3 eram 2D e os outros 4, 3D. Embora os resultados não tenham sido satisfatórios para os datasets 2D, os 3D obtiveram resultados satisfatórios durante a fase de rastreamento, com médias de acurácia variando de 90,1% a 94,4%. A partir da validação, percebeu-se que, mesmo tendo obtido valores satisfatórios, inclusive alguns deles melhores que alguns encontrados no estado da arte, o algoritmo ainda precisa de melhorias.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESSão Cristóvão, SEporComputaçãoProcessamento de imagensTécnicas digitaisCiências médicasCélulasRastreamento de célulasImagens 3DBiomedicinaCell tracking3D imagesImage processingBiomedicineCIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAORastreamento de células em vídeos 3Dinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisPós-Graduação em Ciência da ComputaçãoUFSreponame:Repositório Institucional da UFSinstname:Universidade Federal de Sergipe (UFS)instacron:UFSinfo:eu-repo/semantics/openAccessTEXTDAVY_OLIVEIRA_BARROS_SOUSA.pdf.txtDAVY_OLIVEIRA_BARROS_SOUSA.pdf.txtExtracted texttext/plain144050https://ri.ufs.br/jspui/bitstream/riufs/10782/3/DAVY_OLIVEIRA_BARROS_SOUSA.pdf.txt5f8f9a264d74300c40b377f736fae69aMD53THUMBNAILDAVY_OLIVEIRA_BARROS_SOUSA.pdf.jpgDAVY_OLIVEIRA_BARROS_SOUSA.pdf.jpgGenerated Thumbnailimage/jpeg1305https://ri.ufs.br/jspui/bitstream/riufs/10782/4/DAVY_OLIVEIRA_BARROS_SOUSA.pdf.jpg510a6554f818a5032d684b957e31a09bMD54LICENSElicense.txtlicense.txttext/plain; charset=utf-81475https://ri.ufs.br/jspui/bitstream/riufs/10782/1/license.txt098cbbf65c2c15e1fb2e49c5d306a44cMD51ORIGINALDAVY_OLIVEIRA_BARROS_SOUSA.pdfDAVY_OLIVEIRA_BARROS_SOUSA.pdfapplication/pdf6388595https://ri.ufs.br/jspui/bitstream/riufs/10782/2/DAVY_OLIVEIRA_BARROS_SOUSA.pdf46eeeec5a9939722bd6b5d998360a127MD52riufs/107822019-03-28 20:30:07.476oai:ufs.br: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Repositório InstitucionalPUBhttps://ri.ufs.br/oai/requestrepositorio@academico.ufs.bropendoar:2019-03-28T23:30:07Repositório Institucional da UFS - Universidade Federal de Sergipe (UFS)false |
dc.title.pt_BR.fl_str_mv |
Rastreamento de células em vídeos 3D |
title |
Rastreamento de células em vídeos 3D |
spellingShingle |
Rastreamento de células em vídeos 3D Sousa, Davy Oliveira Barros Computação Processamento de imagens Técnicas digitais Ciências médicas Células Rastreamento de células Imagens 3D Biomedicina Cell tracking 3D images Image processing Biomedicine CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO |
title_short |
Rastreamento de células em vídeos 3D |
title_full |
Rastreamento de células em vídeos 3D |
title_fullStr |
Rastreamento de células em vídeos 3D |
title_full_unstemmed |
Rastreamento de células em vídeos 3D |
title_sort |
Rastreamento de células em vídeos 3D |
author |
Sousa, Davy Oliveira Barros |
author_facet |
Sousa, Davy Oliveira Barros |
author_role |
author |
dc.contributor.author.fl_str_mv |
Sousa, Davy Oliveira Barros |
dc.contributor.advisor1.fl_str_mv |
Macedo, Hendrik Teixeira |
contributor_str_mv |
Macedo, Hendrik Teixeira |
dc.subject.por.fl_str_mv |
Computação Processamento de imagens Técnicas digitais Ciências médicas Células Rastreamento de células Imagens 3D Biomedicina |
topic |
Computação Processamento de imagens Técnicas digitais Ciências médicas Células Rastreamento de células Imagens 3D Biomedicina Cell tracking 3D images Image processing Biomedicine CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO |
dc.subject.eng.fl_str_mv |
Cell tracking 3D images Image processing Biomedicine |
dc.subject.cnpq.fl_str_mv |
CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO |
description |
Performing cell tracking is important for curing and preventing diseases. This is due to the fact that cellular motility is linked to several cellular processes. However, performing the analysis of the trajectory of a cell is not a simple job, because to store the information of the trajectory it is necessary a great amount of images, mainly in 3D images. Thus, it is necessary to create algorithms that can perform cell tracking in a practical and automatic way. In this work was given a continuation of the work of conclusion of course (TCC) of Sousa (2015) in order to improve the tracking algorithm already implemented and presented in Sousa (2015). To overcome the shortcomings of the algorithm implemented by Sousa (2015), modifications were made to the segmentation, labeling and tracking phases. In addition, methods have been added for the detection of cell division and the entry and exit of new cells of the video. The validation of the algorithm was done through an evaluation software that has routines for both the segmentation and the tracking part. 11 datasets were used for the validation, and the proposed algorithm was able to obtain results for 7 of them. Among the 7 datasets, 3 were 2D and the other 4, 3D. Although the results were not satisfactory for the 2D datasets, the 3Ds obtained satisfactory results during the tracking phase, with averages of accuracy ranging from 90.1% to 94.4%. From the validation, it was realized that, even having obtained satisfactory values, including some of them better than some found in the state of the art, the algorithm still needs improvements. |
publishDate |
2018 |
dc.date.issued.fl_str_mv |
2018-08-28 |
dc.date.accessioned.fl_str_mv |
2019-03-28T23:30:07Z |
dc.date.available.fl_str_mv |
2019-03-28T23:30:07Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
SOUSA, Davy Oliveira Barros. Rastreamento de células em vídeos 3D. 2018. 72 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Sergipe, São Cristóvão, SE, 2018. |
dc.identifier.uri.fl_str_mv |
http://ri.ufs.br/jspui/handle/riufs/10782 |
identifier_str_mv |
SOUSA, Davy Oliveira Barros. Rastreamento de células em vídeos 3D. 2018. 72 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Sergipe, São Cristóvão, SE, 2018. |
url |
http://ri.ufs.br/jspui/handle/riufs/10782 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.program.fl_str_mv |
Pós-Graduação em Ciência da Computação |
dc.publisher.initials.fl_str_mv |
UFS |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFS instname:Universidade Federal de Sergipe (UFS) instacron:UFS |
instname_str |
Universidade Federal de Sergipe (UFS) |
instacron_str |
UFS |
institution |
UFS |
reponame_str |
Repositório Institucional da UFS |
collection |
Repositório Institucional da UFS |
bitstream.url.fl_str_mv |
https://ri.ufs.br/jspui/bitstream/riufs/10782/3/DAVY_OLIVEIRA_BARROS_SOUSA.pdf.txt https://ri.ufs.br/jspui/bitstream/riufs/10782/4/DAVY_OLIVEIRA_BARROS_SOUSA.pdf.jpg https://ri.ufs.br/jspui/bitstream/riufs/10782/1/license.txt https://ri.ufs.br/jspui/bitstream/riufs/10782/2/DAVY_OLIVEIRA_BARROS_SOUSA.pdf |
bitstream.checksum.fl_str_mv |
5f8f9a264d74300c40b377f736fae69a 510a6554f818a5032d684b957e31a09b 098cbbf65c2c15e1fb2e49c5d306a44c 46eeeec5a9939722bd6b5d998360a127 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositório Institucional da UFS - Universidade Federal de Sergipe (UFS) |
repository.mail.fl_str_mv |
repositorio@academico.ufs.br |
_version_ |
1802110696855437312 |