3D Convolutional Neural Network for Liver Tumor Segmentation
Main Author: | |
---|---|
Publication Date: | 2018 |
Format: | Master thesis |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | https://hdl.handle.net/10216/114203 |
id |
RCAP_dcca72b82225d35ef10e05336d933da2 |
---|---|
oai_identifier_str |
oai:repositorio-aberto.up.pt:10216/114203 |
network_acronym_str |
RCAP |
network_name_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository_id_str |
https://opendoar.ac.uk/repository/7160 |
spelling |
3D Convolutional Neural Network for Liver Tumor SegmentationEngenharia electrotécnica, electrónica e informáticaElectrical engineering, Electronic engineering, Information engineering2018-07-192018-07-19T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/10216/114203TID:202118320engPedro Diogo da Cunha Amoriminfo: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:RCAAP2025-02-27T19:13:19Zoai:repositorio-aberto.up.pt:10216/114203Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T23:11:32.261936Repositórios 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 |
3D Convolutional Neural Network for Liver Tumor Segmentation |
title |
3D Convolutional Neural Network for Liver Tumor Segmentation |
spellingShingle |
3D Convolutional Neural Network for Liver Tumor Segmentation Pedro Diogo da Cunha Amorim Engenharia electrotécnica, electrónica e informática Electrical engineering, Electronic engineering, Information engineering |
title_short |
3D Convolutional Neural Network for Liver Tumor Segmentation |
title_full |
3D Convolutional Neural Network for Liver Tumor Segmentation |
title_fullStr |
3D Convolutional Neural Network for Liver Tumor Segmentation |
title_full_unstemmed |
3D Convolutional Neural Network for Liver Tumor Segmentation |
title_sort |
3D Convolutional Neural Network for Liver Tumor Segmentation |
author |
Pedro Diogo da Cunha Amorim |
author_facet |
Pedro Diogo da Cunha Amorim |
author_role |
author |
dc.contributor.author.fl_str_mv |
Pedro Diogo da Cunha Amorim |
dc.subject.por.fl_str_mv |
Engenharia electrotécnica, electrónica e informática Electrical engineering, Electronic engineering, Information engineering |
topic |
Engenharia electrotécnica, electrónica e informática Electrical engineering, Electronic engineering, Information engineering |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-07-19 2018-07-19T00:00:00Z |
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 |
https://hdl.handle.net/10216/114203 TID:202118320 |
url |
https://hdl.handle.net/10216/114203 |
identifier_str_mv |
TID:202118320 |
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 |
_version_ |
1833600048593633280 |