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Comparison of different image reconstruction algorithms for Digital Breast Tomosynthesis and assessment of their potential to reduce radiation dose

Bibliographic Details
Main Author: Diogo, Raquel Silva
Publication Date: 2022
Format: Master thesis
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10451/56892
Summary: Tese de mestrado, Engenharia Física, 2022, Universidade de Lisboa, Faculdade de Ciências
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spelling Comparison of different image reconstruction algorithms for Digital Breast Tomosynthesis and assessment of their potential to reduce radiation doseTomossíntese Digital MamáriaFeldkamp Davis and KressSimultaneous Algebraic Reconstruction Technique; Maximum Likelihood Expectation Maximization; Minimização da Variação Total dos DadosMaximum Likelihood Expectation MaximizationMinimização da Variação Total dos DadosTeses de mestrado - 2023Departamento de FísicaTese de mestrado, Engenharia Física, 2022, Universidade de Lisboa, Faculdade de CiênciasDigital Breast Tomosynthesis is a three-dimensional medical imaging technique that allows the view of sectional parts of the breast. Obtaining multiple slices of the breast constitutes an advantage in contrast to conventional mammography examination in view of the increased potential in breast cancer detectability. Conventional mammography, despite being a screening success, has undesirable specificity, sensitivity, and high recall rates owing to the overlapping of tissues. Although this new technique promises better diagnostic results, the acquisition methods and image reconstruction algorithms are still under research. Several articles suggest the use of analytic algorithms. However, more recent articles highlight the iterative algorithm’s potential for increasing image quality when compared to the former. The scope of this dissertation was to test the hypothesis of achieving higher quality images using iterative algorithms acquired with lower doses than those using analytic algorithms. In a first stage, the open-source Tomographic Iterative GPU-based Reconstruction (TIGRE) Toolbox for fast and accurate 3D x-ray image reconstruction was used to reconstruct the images acquired using an acrylic phantom. The algorithms used from the toolbox were the Feldkamp, Davis, and Kress, the Simultaneous Algebraic Reconstruction Technique, and the Maximum Likelihood Expectation Maximization algorithm. In a second and final state, the possibility of further reducing the radiation dose using image postprocessing tools was evaluated. A Total Variation Minimization filter was applied to the images reconstructed with the TIGRE toolbox algorithm that provided the best image quality. These were then compared to the images of the commercial unit used for the image acquisitions. With the use of image quality parameters, it was found that the Maximum Likelihood Expectation Maximization algorithm performance was the best of the three for lower radiation doses, especially with the filter. In sum, the result showed the potential of the algorithm in obtaining images with quality for low doses.Matela, Nuno Miguel de Pinto Lobo e, 1978-Repositório da Universidade de LisboaDiogo, Raquel Silva2023-03-29T12:03:10Z202320222023-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10451/56892TID:203493656enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-17T14:55:38Zoai:repositorio.ulisboa.pt:10451/56892Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T03:29:08.321724Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Comparison of different image reconstruction algorithms for Digital Breast Tomosynthesis and assessment of their potential to reduce radiation dose
title Comparison of different image reconstruction algorithms for Digital Breast Tomosynthesis and assessment of their potential to reduce radiation dose
spellingShingle Comparison of different image reconstruction algorithms for Digital Breast Tomosynthesis and assessment of their potential to reduce radiation dose
Diogo, Raquel Silva
Tomossíntese Digital Mamária
Feldkamp Davis and Kress
Simultaneous Algebraic Reconstruction Technique; Maximum Likelihood Expectation Maximization; Minimização da Variação Total dos Dados
Maximum Likelihood Expectation Maximization
Minimização da Variação Total dos Dados
Teses de mestrado - 2023
Departamento de Física
title_short Comparison of different image reconstruction algorithms for Digital Breast Tomosynthesis and assessment of their potential to reduce radiation dose
title_full Comparison of different image reconstruction algorithms for Digital Breast Tomosynthesis and assessment of their potential to reduce radiation dose
title_fullStr Comparison of different image reconstruction algorithms for Digital Breast Tomosynthesis and assessment of their potential to reduce radiation dose
title_full_unstemmed Comparison of different image reconstruction algorithms for Digital Breast Tomosynthesis and assessment of their potential to reduce radiation dose
title_sort Comparison of different image reconstruction algorithms for Digital Breast Tomosynthesis and assessment of their potential to reduce radiation dose
author Diogo, Raquel Silva
author_facet Diogo, Raquel Silva
author_role author
dc.contributor.none.fl_str_mv Matela, Nuno Miguel de Pinto Lobo e, 1978-
Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Diogo, Raquel Silva
dc.subject.por.fl_str_mv Tomossíntese Digital Mamária
Feldkamp Davis and Kress
Simultaneous Algebraic Reconstruction Technique; Maximum Likelihood Expectation Maximization; Minimização da Variação Total dos Dados
Maximum Likelihood Expectation Maximization
Minimização da Variação Total dos Dados
Teses de mestrado - 2023
Departamento de Física
topic Tomossíntese Digital Mamária
Feldkamp Davis and Kress
Simultaneous Algebraic Reconstruction Technique; Maximum Likelihood Expectation Maximization; Minimização da Variação Total dos Dados
Maximum Likelihood Expectation Maximization
Minimização da Variação Total dos Dados
Teses de mestrado - 2023
Departamento de Física
description Tese de mestrado, Engenharia Física, 2022, Universidade de Lisboa, Faculdade de Ciências
publishDate 2022
dc.date.none.fl_str_mv 2022
2023-03-29T12:03:10Z
2023
2023-01-01T00:00:00Z
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.uri.fl_str_mv http://hdl.handle.net/10451/56892
TID:203493656
url http://hdl.handle.net/10451/56892
identifier_str_mv TID:203493656
dc.language.iso.fl_str_mv eng
language eng
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:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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