3D digital breast cancer models with multimodal fusion algorithms

Detalhes bibliográficos
Autor(a) principal: Bessa, Sílvia
Data de Publicação: 2020
Outros Autores: Gouveia, Pedro F., Carvalho, Pedro H., Rodrigues, Cátia, Silva, Nuno L., Cardoso, Fátima, Cardoso, Jaime S., Oliveira, Hélder P., Cardoso, Maria João
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/147519
Resumo: Funding This work was supported by the ERDFeEuropean Regional Development Fund through the Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement and through the Portuguese National Innovation Agency (ANI) as a part of project BCCT.PlaneNORTE-01- 0247-FEDER-01768 and also by Fundação para a Ciência e a Tecnologia (FCT) within Ph.D grant number SFRH/BD/115616/2016.
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spelling 3D digital breast cancer models with multimodal fusion algorithms3D breast modelBreast cancerFusionMagnetic resonance imagingMultimodal registrationSurfaceSurgerySDG 3 - Good Health and Well-beingFunding This work was supported by the ERDFeEuropean Regional Development Fund through the Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement and through the Portuguese National Innovation Agency (ANI) as a part of project BCCT.PlaneNORTE-01- 0247-FEDER-01768 and also by Fundação para a Ciência e a Tecnologia (FCT) within Ph.D grant number SFRH/BD/115616/2016.Breast cancer image fusion consists of registering and visualizing different sets of a patient synchronized torso and radiological images into a 3D model. Breast spatial interpretation and visualization by the treating physician can be augmented with a patient-specific digital breast model that integrates radiological images. But the absence of a ground truth for a good correlation between surface and radiological information has impaired the development of potential clinical applications. A new image acquisition protocol was designed to acquire breast Magnetic Resonance Imaging (MRI) and 3D surface scan data with surface markers on the patient's breasts and torso. A patient-specific digital breast model integrating the real breast torso and the tumor location was created and validated with a MRI/3D surface scan fusion algorithm in 16 breast cancer patients. This protocol was used to quantify breast shape differences between different modalities, and to measure the target registration error of several variants of the MRI/3D scan fusion algorithm. The fusion of single breasts without the biomechanical model of pose transformation had acceptable registration errors and accurate tumor locations. The performance of the fusion algorithm was not affected by breast volume. Further research and virtual clinical interfaces could lead to fast integration of this fusion technology into clinical practice.NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)RUNBessa, SílviaGouveia, Pedro F.Carvalho, Pedro H.Rodrigues, CátiaSilva, Nuno L.Cardoso, FátimaCardoso, Jaime S.Oliveira, Hélder P.Cardoso, Maria João2023-01-13T22:11:38Z2020-02-012020-02-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article10application/pdfhttp://hdl.handle.net/10362/147519eng0960-9776PURE: 16703119https://doi.org/10.1016/j.breast.2019.12.016info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:28:40Zoai:run.unl.pt:10362/147519Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:52:58.267664Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv 3D digital breast cancer models with multimodal fusion algorithms
title 3D digital breast cancer models with multimodal fusion algorithms
spellingShingle 3D digital breast cancer models with multimodal fusion algorithms
Bessa, Sílvia
3D breast model
Breast cancer
Fusion
Magnetic resonance imaging
Multimodal registration
Surface
Surgery
SDG 3 - Good Health and Well-being
title_short 3D digital breast cancer models with multimodal fusion algorithms
title_full 3D digital breast cancer models with multimodal fusion algorithms
title_fullStr 3D digital breast cancer models with multimodal fusion algorithms
title_full_unstemmed 3D digital breast cancer models with multimodal fusion algorithms
title_sort 3D digital breast cancer models with multimodal fusion algorithms
author Bessa, Sílvia
author_facet Bessa, Sílvia
Gouveia, Pedro F.
Carvalho, Pedro H.
Rodrigues, Cátia
Silva, Nuno L.
Cardoso, Fátima
Cardoso, Jaime S.
Oliveira, Hélder P.
Cardoso, Maria João
author_role author
author2 Gouveia, Pedro F.
Carvalho, Pedro H.
Rodrigues, Cátia
Silva, Nuno L.
Cardoso, Fátima
Cardoso, Jaime S.
Oliveira, Hélder P.
Cardoso, Maria João
author2_role author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)
RUN
dc.contributor.author.fl_str_mv Bessa, Sílvia
Gouveia, Pedro F.
Carvalho, Pedro H.
Rodrigues, Cátia
Silva, Nuno L.
Cardoso, Fátima
Cardoso, Jaime S.
Oliveira, Hélder P.
Cardoso, Maria João
dc.subject.por.fl_str_mv 3D breast model
Breast cancer
Fusion
Magnetic resonance imaging
Multimodal registration
Surface
Surgery
SDG 3 - Good Health and Well-being
topic 3D breast model
Breast cancer
Fusion
Magnetic resonance imaging
Multimodal registration
Surface
Surgery
SDG 3 - Good Health and Well-being
description Funding This work was supported by the ERDFeEuropean Regional Development Fund through the Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement and through the Portuguese National Innovation Agency (ANI) as a part of project BCCT.PlaneNORTE-01- 0247-FEDER-01768 and also by Fundação para a Ciência e a Tecnologia (FCT) within Ph.D grant number SFRH/BD/115616/2016.
publishDate 2020
dc.date.none.fl_str_mv 2020-02-01
2020-02-01T00:00:00Z
2023-01-13T22:11:38Z
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.uri.fl_str_mv http://hdl.handle.net/10362/147519
url http://hdl.handle.net/10362/147519
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0960-9776
PURE: 16703119
https://doi.org/10.1016/j.breast.2019.12.016
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 10
application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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