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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPAW/3RQEQUE
Repositorysid.inpe.br/sibgrapi/2018/09.11.00.20
Last Update2018:09.11.00.20.20 (UTC) natandrade18@hotmail.com
Metadata Repositorysid.inpe.br/sibgrapi/2018/09.11.00.20.20
Metadata Last Update2022:05.18.22.18.31 (UTC) administrator
DOI10.1109/SIBGRAPI.2018.00066
Citation KeyAndradeFariCapp:2018:RiDeLe
TitleA Practical Review on Medical Image Registration: from Rigid to Deep Learning based Approaches
FormatOn-line
Year2018
Access Date2024, Apr. 28
Number of Files1
Size489 KiB
2. Context
Author1 Andrade, Natan
2 Faria, Fabio Augusto
3 Cappabianco, Fábio Augusto Menocci
Affiliation1 Universidade Federal de São Paulo
2 Universidade Federal de São Paulo
3 Universidade Federal de São Paulo
EditorRoss, Arun
Gastal, Eduardo S. L.
Jorge, Joaquim A.
Queiroz, Ricardo L. de
Minetto, Rodrigo
Sarkar, Sudeep
Papa, João Paulo
Oliveira, Manuel M.
Arbeláez, Pablo
Mery, Domingo
Oliveira, Maria Cristina Ferreira de
Spina, Thiago Vallin
Mendes, Caroline Mazetto
Costa, Henrique Sérgio Gutierrez
Mejail, Marta Estela
Geus, Klaus de
Scheer, Sergio
e-Mail Addressnatandrade18@hotmail.com
Conference NameConference on Graphics, Patterns and Images, 31 (SIBGRAPI)
Conference LocationFoz do Iguaçu, PR, Brazil
Date29 Oct.-1 Nov. 2018
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Book TitleProceedings
Tertiary TypeTutorial
History (UTC)2018-09-11 00:20:20 :: natandrade18@hotmail.com -> administrator ::
2022-05-18 22:18:31 :: administrator -> :: 2018
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsImage Registration
Medical Imaging
Deep Learning
AbstractThe large variety of medical image modalities (e.g. Computed Tomography, Magnetic Resonance Imaging, and Positron Emission Tomography) acquired from the same body region of a patient together with recent advances in computer architectures with faster and larger CPUs and GPUs allows a new, exciting, and unexplored world for image registration area. A precise and accurate registration of images makes possible understanding the etiology of diseases, improving surgery planning and execution, detecting otherwise unnoticed health problem signals, and mapping functionalities of the brain. The goal of this paper is to present a review of the state-of-the-art in medical image registration starting from the preprocessing steps, covering the most popular methodologies of the literature and finish with the more recent advances and perspectives from the application of Deep Learning architectures.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2018 > A Practical Review...
doc Directory Contentaccess
source Directory Contentthere are no files
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPAW/3RQEQUE
zipped data URLhttp://urlib.net/zip/8JMKD3MGPAW/3RQEQUE
Languageen
Target FilePaper ID Tutorial-1.pdf
User Groupnatandrade18@hotmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPAW/3RPADUS
Citing Item Listsid.inpe.br/sibgrapi/2018/09.03.20.37 8
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume


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