A novel multi-atlas strategy with dense deformation field reconstruction for abdominal and thoracic multi-organ segmentation from computed tomography
Autor(a) principal: | |
---|---|
Data de Publicação: | 2018 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/11110/1412 |
Resumo: | Anatomical evaluation of multiple abdominal and thoracic organs is generally performed with computed tomography images. Owing to the large field-of-view of these images, automatic segmentation strategies are typically required, facilitating the clinical evaluation. Multi-atlas segmentation (MAS) strategies have been widely used with this process, requiring multiple alignments between the target image and the set of known datasets, and subsequently fusing the alignment results to obtain the final segmentation. Nonetheless, current MAS strategies apply a global alignment of a deformable object, per organ, subdividing the segmentation process into multiple ones and losing the spatial information among nearby organs. This paper presents a novel MAS approach. First, a coarse-to-fine method with multiple global alignments (one per organ) is used. To make the method spatially coherent, these individual organs’ global transformations are then fused in one using a dense deformation field reconstruction strategy. Second, from the candidate segmentations obtained, the final segmentation is estimated through an organ-based label fusion approach. The proposed method is evaluated and compared against a conventional MAS strategy through the segmentation of twelve abdominal and thoracic organs from the VISCERAL Anatomy bench- mark. Average Dice coefficients for the liver, spleen, lungs and kidneys are all higher than 90%, are around 85% for the aorta, trachea and sternum and 70% for the pancreas, urinary bladder and gallbladder. The novel MAS strategy, with dense deformation field reconstruction, shows competitive results against other state-of-the-art methods, proving its added value for the segmentation of abdominal and thoracic organs, mainly for highly variable organs. |
id |
RCAP_30f0e26619f4fc28d321ae1e9cb325ca |
---|---|
oai_identifier_str |
oai:ciencipca.ipca.pt:11110/1412 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
spelling |
A novel multi-atlas strategy with dense deformation field reconstruction for abdominal and thoracic multi-organ segmentation from computed tomographyMulti-atlas segmentationCoarse-to-fine registrationAbdominal/thoracic CTDense deformation field reconstructionAnatomical evaluation of multiple abdominal and thoracic organs is generally performed with computed tomography images. Owing to the large field-of-view of these images, automatic segmentation strategies are typically required, facilitating the clinical evaluation. Multi-atlas segmentation (MAS) strategies have been widely used with this process, requiring multiple alignments between the target image and the set of known datasets, and subsequently fusing the alignment results to obtain the final segmentation. Nonetheless, current MAS strategies apply a global alignment of a deformable object, per organ, subdividing the segmentation process into multiple ones and losing the spatial information among nearby organs. This paper presents a novel MAS approach. First, a coarse-to-fine method with multiple global alignments (one per organ) is used. To make the method spatially coherent, these individual organs’ global transformations are then fused in one using a dense deformation field reconstruction strategy. Second, from the candidate segmentations obtained, the final segmentation is estimated through an organ-based label fusion approach. The proposed method is evaluated and compared against a conventional MAS strategy through the segmentation of twelve abdominal and thoracic organs from the VISCERAL Anatomy bench- mark. Average Dice coefficients for the liver, spleen, lungs and kidneys are all higher than 90%, are around 85% for the aorta, trachea and sternum and 70% for the pancreas, urinary bladder and gallbladder. The novel MAS strategy, with dense deformation field reconstruction, shows competitive results against other state-of-the-art methods, proving its added value for the segmentation of abdominal and thoracic organs, mainly for highly variable organs.The authors acknowledge Fundação para a Ciência e a Tecnologia (FCT), Portugal and the European Social Found, European Union, for funding support through the “Programa Op- eracional Capital Humano” (POCH) in the scope of the PhD grants SFRH/BD/93443/2013 (S. Queirós), SFRH/BD/95438/2013 (P. Morais), and PD/BDE/113597/2015 (J. Gomes-Fonseca). Moreover, authors gratefully acknowledge the funding of the projects NORTE-01-0145-FEDER-000013 and NORTE-01-0145- FEDER-024300, supported by Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER). This work has been funded by FEDER funds, through the Competitiveness Factors Operational Programme (COMPETE), and by National funds, through the Foundation for Science and Technology (FCT), under the scope of the project POCI-01-0145-FEDER- 007038.Medical Image Analysis2018-09-12T13:44:30Z2018-02-02T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/11110/1412oai:ciencipca.ipca.pt:11110/1412eng1361-8415https://doi.org/DOI: https://doi.org/10.1016/j.media.2018.02.001http://hdl.handle.net/11110/1412metadata only accessinfo:eu-repo/semantics/openAccessOliveira, BrunoQueirós, SandroMorais, PedroTorres, HelenaFonseca, JoãoFonseca, JaimeVilaça, Joãoreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2022-09-05T12:52:49Zoai:ciencipca.ipca.pt:11110/1412Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T15:01:45.658529Repositório 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 |
A novel multi-atlas strategy with dense deformation field reconstruction for abdominal and thoracic multi-organ segmentation from computed tomography |
title |
A novel multi-atlas strategy with dense deformation field reconstruction for abdominal and thoracic multi-organ segmentation from computed tomography |
spellingShingle |
A novel multi-atlas strategy with dense deformation field reconstruction for abdominal and thoracic multi-organ segmentation from computed tomography Oliveira, Bruno Multi-atlas segmentation Coarse-to-fine registration Abdominal/thoracic CT Dense deformation field reconstruction |
title_short |
A novel multi-atlas strategy with dense deformation field reconstruction for abdominal and thoracic multi-organ segmentation from computed tomography |
title_full |
A novel multi-atlas strategy with dense deformation field reconstruction for abdominal and thoracic multi-organ segmentation from computed tomography |
title_fullStr |
A novel multi-atlas strategy with dense deformation field reconstruction for abdominal and thoracic multi-organ segmentation from computed tomography |
title_full_unstemmed |
A novel multi-atlas strategy with dense deformation field reconstruction for abdominal and thoracic multi-organ segmentation from computed tomography |
title_sort |
A novel multi-atlas strategy with dense deformation field reconstruction for abdominal and thoracic multi-organ segmentation from computed tomography |
author |
Oliveira, Bruno |
author_facet |
Oliveira, Bruno Queirós, Sandro Morais, Pedro Torres, Helena Fonseca, João Fonseca, Jaime Vilaça, João |
author_role |
author |
author2 |
Queirós, Sandro Morais, Pedro Torres, Helena Fonseca, João Fonseca, Jaime Vilaça, João |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Oliveira, Bruno Queirós, Sandro Morais, Pedro Torres, Helena Fonseca, João Fonseca, Jaime Vilaça, João |
dc.subject.por.fl_str_mv |
Multi-atlas segmentation Coarse-to-fine registration Abdominal/thoracic CT Dense deformation field reconstruction |
topic |
Multi-atlas segmentation Coarse-to-fine registration Abdominal/thoracic CT Dense deformation field reconstruction |
description |
Anatomical evaluation of multiple abdominal and thoracic organs is generally performed with computed tomography images. Owing to the large field-of-view of these images, automatic segmentation strategies are typically required, facilitating the clinical evaluation. Multi-atlas segmentation (MAS) strategies have been widely used with this process, requiring multiple alignments between the target image and the set of known datasets, and subsequently fusing the alignment results to obtain the final segmentation. Nonetheless, current MAS strategies apply a global alignment of a deformable object, per organ, subdividing the segmentation process into multiple ones and losing the spatial information among nearby organs. This paper presents a novel MAS approach. First, a coarse-to-fine method with multiple global alignments (one per organ) is used. To make the method spatially coherent, these individual organs’ global transformations are then fused in one using a dense deformation field reconstruction strategy. Second, from the candidate segmentations obtained, the final segmentation is estimated through an organ-based label fusion approach. The proposed method is evaluated and compared against a conventional MAS strategy through the segmentation of twelve abdominal and thoracic organs from the VISCERAL Anatomy bench- mark. Average Dice coefficients for the liver, spleen, lungs and kidneys are all higher than 90%, are around 85% for the aorta, trachea and sternum and 70% for the pancreas, urinary bladder and gallbladder. The novel MAS strategy, with dense deformation field reconstruction, shows competitive results against other state-of-the-art methods, proving its added value for the segmentation of abdominal and thoracic organs, mainly for highly variable organs. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-09-12T13:44:30Z 2018-02-02T00:00:00Z |
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/11110/1412 oai:ciencipca.ipca.pt:11110/1412 |
url |
http://hdl.handle.net/11110/1412 |
identifier_str_mv |
oai:ciencipca.ipca.pt:11110/1412 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1361-8415 https://doi.org/DOI: https://doi.org/10.1016/j.media.2018.02.001 http://hdl.handle.net/11110/1412 |
dc.rights.driver.fl_str_mv |
metadata only access info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
metadata only access |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Medical Image Analysis |
publisher.none.fl_str_mv |
Medical Image Analysis |
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 |
|
_version_ |
1799129887425953792 |