Avaliação comparativa de métodos de reconstrução inversa
Ano de defesa: | 2023 |
---|---|
Autor(a) principal: | |
Outros Autores: | |
Orientador(a): | |
Banca de defesa: | , |
Tipo de documento: | Dissertação |
Tipo de acesso: | Acesso aberto |
Idioma: | por |
Instituição de defesa: |
Universidade do Estado do Rio de Janeiro
|
Programa de Pós-Graduação: |
Programa de Pós-Graduação em Engenharia Eletrônica
|
Departamento: |
Centro de Tecnologia e Ciências::Faculdade de Engenharia
|
País: |
Brasil
|
Palavras-chave em Português: | |
Palavras-chave em Inglês: | |
Área do conhecimento CNPq: | |
Link de acesso: | http://www.bdtd.uerj.br/handle/1/20937 |
Resumo: | This dissertation compares tomographic reconstruction algorithms. Sixteen reconstruction algorithms from five classes, with different models and operating principles, were studied and compared using descriptive, quantitative, and qualitative criteria. Firstly, in the descriptive comparison, the algorithms were grouped according to their common elements. That is, the classes and their fundamental characteristics are presented. The data set used for the quantitative evaluation is generated from three (3) complete base images, which have different qualitative characteristics to consider application groups that are not correlated with each other: health, architecture, and industry. We obtain a group of 60 projection sets (sinograms) from the 03 base images through a simulated acquisition process with progressive corruption. Corruption occurs by directly adding Gaussian noise to a single part of the acquisition process at a time, either in the full image of the target object or in the full image of the sinogram. The first approach accommodates applications where the error is associated with propagation phenomena and the interaction of the probe beams with the target object. In contrast, the second approach accommodates applications where the error is associated with the measurement process. For each algorithm iteration, a reconstruction image corresponding to a sinogram of the set is obtained. When applicable to the algorithm, 50 iterations are used. The quantitative analysis uses different image quality measures to compare the reconstructions. An Aggregate Quality Index is proposed in order to condense the information obtained. We assess the computational cost of the reconstruction based on the processing time of one iteration (the first). Finally, the qualitative comparison evaluates sections of the reconstructions of the images obtained in the sequence of iterations of the algorithm. The discernment of structures (changes in values, speed or inclination, and oscillations when they occur) is evaluated by inspection and statistical indices: Mean, Standard Deviation, and Otsu threshold. The evaluation indicates that algorithms based on likelihood function maximization are more effective (quality) and stable (the quality trend as iterations progress and error is added shows to be monotonous), with a reasonable efficiency compromise (computational cost). The results also suggest criteria for choosing the appropriate reconstruction methods for different application scenarios and suggestions for improving some algorithms. |
id |
UERJ_c9feb20b010c49c4a98dbc2ba098a23a |
---|---|
oai_identifier_str |
oai:www.bdtd.uerj.br:1/20937 |
network_acronym_str |
UERJ |
network_name_str |
Biblioteca Digital de Teses e Dissertações da UERJ |
repository_id_str |
|
spelling |
Lovisolo, Lisandrohttp://lattes.cnpq.br/5556212442729541Tcheou, Michel Pompeuhttp://lattes.cnpq.br/9868296846852777Henriques, Felipe da Rochahttp://lattes.cnpq.br/1357873484696487http://lattes.cnpq.br/2913311442320205Fontes, Allan de Oliveiraallandeof@gmail.com2024-01-17T15:52:38Z2023-05-29FONTES, Allan de Oliveira. Avaliação comparativa de métodos de reconstrução inversa. 2023. 416 f. Dissertação (Mestrado em Engenharia Eletrônica) - Faculdade de Engenharia, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, 2023.http://www.bdtd.uerj.br/handle/1/20937This dissertation compares tomographic reconstruction algorithms. Sixteen reconstruction algorithms from five classes, with different models and operating principles, were studied and compared using descriptive, quantitative, and qualitative criteria. Firstly, in the descriptive comparison, the algorithms were grouped according to their common elements. That is, the classes and their fundamental characteristics are presented. The data set used for the quantitative evaluation is generated from three (3) complete base images, which have different qualitative characteristics to consider application groups that are not correlated with each other: health, architecture, and industry. We obtain a group of 60 projection sets (sinograms) from the 03 base images through a simulated acquisition process with progressive corruption. Corruption occurs by directly adding Gaussian noise to a single part of the acquisition process at a time, either in the full image of the target object or in the full image of the sinogram. The first approach accommodates applications where the error is associated with propagation phenomena and the interaction of the probe beams with the target object. In contrast, the second approach accommodates applications where the error is associated with the measurement process. For each algorithm iteration, a reconstruction image corresponding to a sinogram of the set is obtained. When applicable to the algorithm, 50 iterations are used. The quantitative analysis uses different image quality measures to compare the reconstructions. An Aggregate Quality Index is proposed in order to condense the information obtained. We assess the computational cost of the reconstruction based on the processing time of one iteration (the first). Finally, the qualitative comparison evaluates sections of the reconstructions of the images obtained in the sequence of iterations of the algorithm. The discernment of structures (changes in values, speed or inclination, and oscillations when they occur) is evaluated by inspection and statistical indices: Mean, Standard Deviation, and Otsu threshold. The evaluation indicates that algorithms based on likelihood function maximization are more effective (quality) and stable (the quality trend as iterations progress and error is added shows to be monotonous), with a reasonable efficiency compromise (computational cost). The results also suggest criteria for choosing the appropriate reconstruction methods for different application scenarios and suggestions for improving some algorithms.Esta dissertação compara algoritmos de reconstrução tomográfica. Dezesseis algoritmos de reconstrução advindos de cinco classes, com modelos e princípios de funcionamento distintos foram estudados e comparados por meio de critérios descritivos, quantitativos e qualitativos. Na comparação descritiva, os algoritmos foram agrupados de acordo com seus elementos comuns, isto é, as classes, e suas características fundamentais são apresentadas. O conjunto de dados usado para a avaliação quantitativa é gerado a partir de três (3) imagens base íntegras, que apresentam características qualitativas distintas de forma a considerar grupos de aplicação não correlacionados entre si: saúde, arquitetura e indústria. Um grupo de 60 projeções (sinogramas) é obtido à partir das 03 imagens-base, por meio de um processo de aquisição simulada com corrupção progressiva. A corrupção ocorre pela adição direta de ruído gaussiano em uma única parte do processo de aquisição por vez, seja na imagem íntegra do objeto-alvo ou no sinograma íntegro. A primeira abordagem visa acomodar aplicações onde o erro mostra-se associado a fenômenos de propagação e interação dos feixes de sondagem com o objeto-alvo, já a segunda abordagem visa acomodar aplicações onde o erro mostra-se associado ao processo de medição. Para cada iteração de um algoritmo de reconstrução, obtém-se a imagem de reconstrução correspondente a cada um dos sinogramas do conjunto. Quando aplicável ao algoritmo, 50 iterações são utilizadas. Na análise quantitativa, diferentes medidas de qualidade de imagem são utilizadas para comparar as reconstruções. Um Índice de Qualidade Agregado é proposto de forma a condensar as informações obtidas. Aferimos o custo computacional da reconstrução, a partir do tempo de processamento de uma iteração (a primeira). Por último, a comparação qualitativa avalia cortes das reconstruções das imagens obtidas na sequência de iterações do algoritmo. Avalia-se o discernimento das estruturas (mudanças de valores, velocidade ou inclinação, e oscilações quando elas ocorrem) por inspeção e por índices estatísticos: Média, Desvio Padrão e limiar de Otsu. A avaliação indica que os algoritmos baseados maximização da função de verossimilhança são mais eficazes (qualidade) e estáveis (a tendência de qualidade conforme as iterações avançam e erro é adicionado mostra se monótona), com um bom compromisso de eficiência (custo computacional). Os resultados permitem ainda sugerir critérios de escolha dos métodos de reconstrução apropriados para diferentes cenários de aplicação e sugestões de direções para aperfeiçoamento de alguns algoritmos.Submitted by Julia CTC/B (julia.vieira@uerj.br) on 2024-01-17T15:52:38Z No. of bitstreams: 1 Dissertação - Allan de Oliveira Fontes - 2023 - Completo.pdf: 29591326 bytes, checksum: 9afb2ae4cfa516ee5da1b4fbf2bb7d70 (MD5)Made available in DSpace on 2024-01-17T15:52:38Z (GMT). No. of bitstreams: 1 Dissertação - Allan de Oliveira Fontes - 2023 - Completo.pdf: 29591326 bytes, checksum: 9afb2ae4cfa516ee5da1b4fbf2bb7d70 (MD5) Previous issue date: 2023-05-29application/pdfporUniversidade do Estado do Rio de JaneiroPrograma de Pós-Graduação em Engenharia EletrônicaUERJBrasilCentro de Tecnologia e Ciências::Faculdade de EngenhariaElectronic engineeringAlgorithmsImage processingPerformance - EvaluationEngenharia eletrônicaAlgorítmosProcessamento de imagensDesempenho - AvaliaçãoENGENHARIAS::ENGENHARIA ELETRICA::TELECOMUNICACOESAvaliação comparativa de métodos de reconstrução inversaComparative evaluation of inverse reconstruction methodsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da UERJinstname:Universidade do Estado do Rio de Janeiro (UERJ)instacron:UERJORIGINALDissertação - Allan de Oliveira Fontes - 2023 - Completo.pdfDissertação - Allan de Oliveira Fontes - 2023 - Completo.pdfapplication/pdf29591326http://www.bdtd.uerj.br/bitstream/1/20937/2/Disserta%C3%A7%C3%A3o+-+Allan+de+Oliveira+Fontes+-+2023+-+Completo.pdf9afb2ae4cfa516ee5da1b4fbf2bb7d70MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-82123http://www.bdtd.uerj.br/bitstream/1/20937/1/license.txte5502652da718045d7fcd832b79fca29MD511/209372024-02-27 15:16:49.778oai:www.bdtd.uerj.br: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Biblioteca Digital de Teses e Dissertaçõeshttp://www.bdtd.uerj.br/PUBhttps://www.bdtd.uerj.br:8443/oai/requestbdtd.suporte@uerj.bropendoar:29032024-02-27T18:16:49Biblioteca Digital de Teses e Dissertações da UERJ - Universidade do Estado do Rio de Janeiro (UERJ)false |
dc.title.por.fl_str_mv |
Avaliação comparativa de métodos de reconstrução inversa |
dc.title.alternative.eng.fl_str_mv |
Comparative evaluation of inverse reconstruction methods |
title |
Avaliação comparativa de métodos de reconstrução inversa |
spellingShingle |
Avaliação comparativa de métodos de reconstrução inversa Fontes, Allan de Oliveira Electronic engineering Algorithms Image processing Performance - Evaluation Engenharia eletrônica Algorítmos Processamento de imagens Desempenho - Avaliação ENGENHARIAS::ENGENHARIA ELETRICA::TELECOMUNICACOES |
title_short |
Avaliação comparativa de métodos de reconstrução inversa |
title_full |
Avaliação comparativa de métodos de reconstrução inversa |
title_fullStr |
Avaliação comparativa de métodos de reconstrução inversa |
title_full_unstemmed |
Avaliação comparativa de métodos de reconstrução inversa |
title_sort |
Avaliação comparativa de métodos de reconstrução inversa |
author |
Fontes, Allan de Oliveira |
author_facet |
Fontes, Allan de Oliveira allandeof@gmail.com |
author_role |
author |
author2 |
allandeof@gmail.com |
author2_role |
author |
dc.contributor.advisor1.fl_str_mv |
Lovisolo, Lisandro |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/5556212442729541 |
dc.contributor.referee1.fl_str_mv |
Tcheou, Michel Pompeu |
dc.contributor.referee1Lattes.fl_str_mv |
http://lattes.cnpq.br/9868296846852777 |
dc.contributor.referee2.fl_str_mv |
Henriques, Felipe da Rocha |
dc.contributor.referee2Lattes.fl_str_mv |
http://lattes.cnpq.br/1357873484696487 |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/2913311442320205 |
dc.contributor.author.fl_str_mv |
Fontes, Allan de Oliveira allandeof@gmail.com |
contributor_str_mv |
Lovisolo, Lisandro Tcheou, Michel Pompeu Henriques, Felipe da Rocha |
dc.subject.eng.fl_str_mv |
Electronic engineering Algorithms Image processing Performance - Evaluation |
topic |
Electronic engineering Algorithms Image processing Performance - Evaluation Engenharia eletrônica Algorítmos Processamento de imagens Desempenho - Avaliação ENGENHARIAS::ENGENHARIA ELETRICA::TELECOMUNICACOES |
dc.subject.por.fl_str_mv |
Engenharia eletrônica Algorítmos Processamento de imagens Desempenho - Avaliação |
dc.subject.cnpq.fl_str_mv |
ENGENHARIAS::ENGENHARIA ELETRICA::TELECOMUNICACOES |
description |
This dissertation compares tomographic reconstruction algorithms. Sixteen reconstruction algorithms from five classes, with different models and operating principles, were studied and compared using descriptive, quantitative, and qualitative criteria. Firstly, in the descriptive comparison, the algorithms were grouped according to their common elements. That is, the classes and their fundamental characteristics are presented. The data set used for the quantitative evaluation is generated from three (3) complete base images, which have different qualitative characteristics to consider application groups that are not correlated with each other: health, architecture, and industry. We obtain a group of 60 projection sets (sinograms) from the 03 base images through a simulated acquisition process with progressive corruption. Corruption occurs by directly adding Gaussian noise to a single part of the acquisition process at a time, either in the full image of the target object or in the full image of the sinogram. The first approach accommodates applications where the error is associated with propagation phenomena and the interaction of the probe beams with the target object. In contrast, the second approach accommodates applications where the error is associated with the measurement process. For each algorithm iteration, a reconstruction image corresponding to a sinogram of the set is obtained. When applicable to the algorithm, 50 iterations are used. The quantitative analysis uses different image quality measures to compare the reconstructions. An Aggregate Quality Index is proposed in order to condense the information obtained. We assess the computational cost of the reconstruction based on the processing time of one iteration (the first). Finally, the qualitative comparison evaluates sections of the reconstructions of the images obtained in the sequence of iterations of the algorithm. The discernment of structures (changes in values, speed or inclination, and oscillations when they occur) is evaluated by inspection and statistical indices: Mean, Standard Deviation, and Otsu threshold. The evaluation indicates that algorithms based on likelihood function maximization are more effective (quality) and stable (the quality trend as iterations progress and error is added shows to be monotonous), with a reasonable efficiency compromise (computational cost). The results also suggest criteria for choosing the appropriate reconstruction methods for different application scenarios and suggestions for improving some algorithms. |
publishDate |
2023 |
dc.date.issued.fl_str_mv |
2023-05-29 |
dc.date.accessioned.fl_str_mv |
2024-01-17T15:52:38Z |
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 |
FONTES, Allan de Oliveira. Avaliação comparativa de métodos de reconstrução inversa. 2023. 416 f. Dissertação (Mestrado em Engenharia Eletrônica) - Faculdade de Engenharia, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, 2023. |
dc.identifier.uri.fl_str_mv |
http://www.bdtd.uerj.br/handle/1/20937 |
identifier_str_mv |
FONTES, Allan de Oliveira. Avaliação comparativa de métodos de reconstrução inversa. 2023. 416 f. Dissertação (Mestrado em Engenharia Eletrônica) - Faculdade de Engenharia, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, 2023. |
url |
http://www.bdtd.uerj.br/handle/1/20937 |
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.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade do Estado do Rio de Janeiro |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Engenharia Eletrônica |
dc.publisher.initials.fl_str_mv |
UERJ |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Centro de Tecnologia e Ciências::Faculdade de Engenharia |
publisher.none.fl_str_mv |
Universidade do Estado do Rio de Janeiro |
dc.source.none.fl_str_mv |
reponame:Biblioteca Digital de Teses e Dissertações da UERJ instname:Universidade do Estado do Rio de Janeiro (UERJ) instacron:UERJ |
instname_str |
Universidade do Estado do Rio de Janeiro (UERJ) |
instacron_str |
UERJ |
institution |
UERJ |
reponame_str |
Biblioteca Digital de Teses e Dissertações da UERJ |
collection |
Biblioteca Digital de Teses e Dissertações da UERJ |
bitstream.url.fl_str_mv |
http://www.bdtd.uerj.br/bitstream/1/20937/2/Disserta%C3%A7%C3%A3o+-+Allan+de+Oliveira+Fontes+-+2023+-+Completo.pdf http://www.bdtd.uerj.br/bitstream/1/20937/1/license.txt |
bitstream.checksum.fl_str_mv |
9afb2ae4cfa516ee5da1b4fbf2bb7d70 e5502652da718045d7fcd832b79fca29 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 |
repository.name.fl_str_mv |
Biblioteca Digital de Teses e Dissertações da UERJ - Universidade do Estado do Rio de Janeiro (UERJ) |
repository.mail.fl_str_mv |
bdtd.suporte@uerj.br |
_version_ |
1792352246611050496 |