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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/45D2P52
Repositorysid.inpe.br/sibgrapi/2021/09.07.03.09
Last Update2021:09.07.03.09.24 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2021/09.07.03.09.24
Metadata Last Update2022:06.14.00.00.32 (UTC) administrator
DOI10.1109/SIBGRAPI54419.2021.00026
Citation KeyAlmeidaPerRenCavSij:2021:ApDeLo
TitleThe gated recurrent conditional generative adversarial network (GRC-GAN): application to denoising of low-dose CT images
FormatOn-line
Year2021
Access Date2024, Sep. 08
Number of Files1
Size1700 KiB
2. Context
Author1 Almeida, Mateus Baltazar
2 Pereira, Luis F. Alves
3 Ren, Tsang Ing
4 Cavalcanti, George D. C.
5 Sijbers, Jan
Affiliation1 Universidade Federal do Agreste de Pernambuco  
2 Universidade Federal do Agreste de Pernambuco  
3 Universidade Federal de Pernambuco  
4 Universidade Federal de Pernambuco  
5 University of Antwerp
EditorPaiva, Afonso
Menotti, David
Baranoski, Gladimir V. G.
Proença, Hugo Pedro
Junior, Antonio Lopes Apolinario
Papa, João Paulo
Pagliosa, Paulo
dos Santos, Thiago Oliveira
e Sá, Asla Medeiros
da Silveira, Thiago Lopes Trugillo
Brazil, Emilio Vital
Ponti, Moacir A.
Fernandes, Leandro A. F.
Avila, Sandra
e-Mail Addressmateusbaltazar9@gmail.com
Conference NameConference on Graphics, Patterns and Images, 34 (SIBGRAPI)
Conference LocationGramado, RS, Brazil (virtual)
Date18-22 Oct. 2021
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2021-09-07 03:09:25 :: mateusbaltazar9@gmail.com -> administrator ::
2022-03-02 00:54:16 :: administrator -> menottid@gmail.com :: 2021
2022-03-02 13:18:19 :: menottid@gmail.com -> administrator :: 2021
2022-06-14 00:00:32 :: administrator -> :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsadversarial networks
gated unit
denoising
AbstractThe ionizing radiation that propagates through the human body at Computed Tomography (CT) exams is known to be carcinogenic. For this reason, the development of methods for image reconstruction that operate with reduced radiation doses is essential. If we reduce the electrical current in the electrically powered X-ray tubes of CT scanners, the amount of radiation that passes through the human body during a CT exam is reduced. However, significant image noise emerges in the reconstructed CT slices if standard reconstruction methods are applied. To estimate routine-dose CT images from low-dose CT images and thus reduce noise, the Conditional Generative Adversarial Network (cGAN) was recently proposed in the literature. In this work, we introduce the Gated Recurrent Conditional Generative Adversarial Network (GRC-GAN) that is based on the usage of network gates to learn the specific regions of the input image to be updated using the cGAN denoising operation. Moreover, the GRC-GAN is executed recurrently in multiple time steps. At each time step, different parts of the input image are denoised. As a result, our GRC-GAN better focus on the denoise criterium than the regular cGAN in the LoDoPaB-CT benchmark.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2021 > The gated recurrent...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > The gated recurrent...
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4. Conditions of access and use
data URLhttp://sibgrapi.sid.inpe.br/ibi/8JMKD3MGPEW34M/45D2P52
zipped data URLhttp://sibgrapi.sid.inpe.br/zip/8JMKD3MGPEW34M/45D2P52
Languageen
Target File40.pdf
User Groupmateusbaltazar9@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/45PQ3RS
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2021/11.12.11.46 50
sid.inpe.br/sibgrapi/2022/06.10.21.49 3
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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