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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/45D397B
Repositorysid.inpe.br/sibgrapi/2021/09.07.05.48
Last Update2021:09.07.05.49.54 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2021/09.07.05.48.30
Metadata Last Update2022:06.14.00.00.33 (UTC) administrator
DOI10.1109/SIBGRAPI54419.2021.00020
Citation KeyChaparro-CruzMont:2021:BoSuDe
TitleBORDE: Boundary and Sub-Region Denormalization for Semantic Brain Image Synthesis
FormatOn-line
Year2021
Access Date2025, Feb. 05
Number of Files1
Size3240 KiB
2. Context
Author1 Chaparro-Cruz, Israel N.
2 Montoya-Zegarra, Javier A.
Affiliation1 Department of Computer Science, Universidad Católica San Pablo, Arequipa, Perú
2 Institute for Biomedical Engineering, ETH Zurich, Zurich, Switzerland
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 Addressisrael.chaparro@ucsp.edu.pe
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 05:49:55 :: israel.chaparro@ucsp.edu.pe -> administrator :: 2021
2022-03-02 00:54:16 :: administrator -> menottid@gmail.com :: 2021
2022-03-02 13:23:16 :: menottid@gmail.com -> administrator :: 2021
2022-06-14 00:00:33 :: administrator -> :: 2021
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsbrain imaging
generative adversarial networks
normalization layers
semantic image synthesis
AbstractMedical images are often expensive to acquire and offer limited use due to legal issues besides the lack of consistency and availability of image annotations. Thus, the use of medical datasets can be restrictive for training deep learning models. The generation of synthetic images along with their corresponding annotations can therefore aid to solve this issue. In this paper, we propose a novel Generative Adversarial Network (GAN) generator for multimodal semantic image synthesis of brain images based on a novel denormalization block named BOundary and sub-Region DEnormalization (BORDE). The new architecture consists of a decoder generator that allows: (i) an effectively sequential propagation of a-priori semantic information through the generator, (ii) noise injection at different scales to avoid mode-collapse, and (iii) the generation of rich and diverse multimodal synthetic samples along with their contours. Our model generates very realistic and plausible synthetic images that when combined with real data helps to improve the accuracy in brain segmentation tasks. Quantitative and qualitative results on challenging multimodal brain imaging datasets (BraTS 2020 and ISLES 2018) demonstrate the advantages of our model over existing image-agnostic state-of-the-art techniques, improving segmentation and semantic image synthesis tasks. This allows us to prove the need for more domain-specific techniques in GANs models.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2021 > BORDE: Boundary and...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/45D397B
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/45D397B
Languageen
Target File70.pdf
User Groupisrael.chaparro@ucsp.edu.pe
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/2021/11.12.11.46 121
sid.inpe.br/sibgrapi/2022/06.10.21.49 6
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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