Publicação
Comparison of different image reconstruction algorithms for Digital Breast Tomosynthesis and assessment of their potential to reduce radiation dose
| Resumo: | Digital 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. |
|---|---|
| Autores principais: | Diogo, Raquel Silva |
| Assunto: | 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 |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório da Universidade de Lisboa |
| _version_ | 1865920815160098816 |
|---|---|
| author | Diogo, Raquel Silva |
| author_facet | Diogo, Raquel Silva Diogo, Raquel Silva |
| author_role | author |
| contributor_name_str_mv | Matela, Nuno Miguel de Pinto Lobo e, 1978- Repositório Científico de Acesso Aberto da ULisboa |
| country_str | PT |
| creators_json_str | [{\"Person.name\":\"Diogo, Raquel Silva\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Matela, Nuno Miguel de Pinto Lobo e, 1978- Repositório Científico de Acesso Aberto da ULisboa |
| datacite.creators.creator.creatorName.fl_str_mv | Diogo, Raquel Silva |
| datacite.date.Accepted.fl_str_mv | 2023-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2023-03-29T12:03:10Z |
| datacite.date.embargoed.fl_str_mv | 2023-03-29T12:03:10Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.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 |
| datacite.titles.title.fl_str_mv | Comparison of different image reconstruction algorithms for Digital Breast Tomosynthesis and assessment of their potential to reduce radiation dose |
| dc.contributor.none.fl_str_mv | Matela, Nuno Miguel de Pinto Lobo e, 1978- Repositório Científico de Acesso Aberto da ULisboa |
| dc.creator.none.fl_str_mv | Diogo, Raquel Silva |
| dc.date.Accepted.fl_str_mv | 2023-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2023-03-29T12:03:10Z |
| dc.date.embargoed.fl_str_mv | 2023-03-29T12:03:10Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10451/56892 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.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 |
| dc.title.fl_str_mv | Comparison of different image reconstruction algorithms for Digital Breast Tomosynthesis and assessment of their potential to reduce radiation dose |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_bdcc |
| description | Digital 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. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | masterThesis |
| fulltext.url.fl_str_mv | https://repositorio.ulisboa.pt/bitstreams/f6f115af-ba66-40e5-8345-f07345d2a6bb/download |
| id | ul_8bed5843f00a60ab583ec9bdee72ddc6 |
| identifier.url.fl_str_mv | http://hdl.handle.net/10451/56892 |
| instacron_str | ul |
| institution | Universidade de Lisboa |
| instname_str | Universidade de Lisboa |
| language | eng |
| network_acronym_str | ul |
| network_name_str | Repositório da Universidade de Lisboa |
| oai_identifier_str | oai:repositorio.ulisboa.pt:10451/56892 |
| organization_str_mv | urn:organizationAcronym:ul |
| person_str_mv | Diogo, Raquel Silva |
| publishDate | 2023 |
| reponame_str | Repositório da Universidade de Lisboa |
| repository_id_str | urn:repositoryAcronym:ul |
| service_str_mv | urn:repositoryAcronym:ul |
| spelling | engpt_PTDigital 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.application/pdfpt_PTComparison of different image reconstruction algorithms for Digital Breast Tomosynthesis and assessment of their potential to reduce radiation doseDiogo, Raquel SilvaMatela, Nuno Miguel de Pinto Lobo e, 1978-HostingInstitutionOrganizationalRepositório Científico de Acesso Aberto da ULisboae-mailmailto:repositorio@reitoria.ulisboa.ptrepositorio@reitoria.ulisboa.ptURNurn:tid:2034936562023-03-29T12:03:10Z202320222023-01-01T00:00:00ZHandlehttp://hdl.handle.net/10451/56892http://purl.org/coar/access_right/c_abf2open accessTomossíntese 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 - 20232178050 bytesliteraturehttp://purl.org/coar/resource_type/c_bdccmaster thesishttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://repositorio.ulisboa.pt/bitstreams/f6f115af-ba66-40e5-8345-f07345d2a6bb/download |
| spellingShingle | Comparison of different image reconstruction algorithms for Digital Breast Tomosynthesis and assessment of their potential to reduce radiation dose 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 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 |
| status | SINGLETON |
| subject.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 |
| title | 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 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 Comparison of different image reconstruction algorithms for Digital Breast Tomosynthesis and assessment of their potential to reduce radiation dose |
| title_short | 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 |
| 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 |
| topic_facet | 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 |
| url | http://hdl.handle.net/10451/56892 |
| visible | 1 |