DEEP LEARNING BASED UV FACIAL IMAGING GENERATION

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dc.contributorSistema FMUSP-HC: Faculdade de Medicina da Universidade de São Paulo (FMUSP) e Hospital das Clínicas da FMUSP
dc.contributor.authorMARGALEF, Pablo Toledo
dc.contributor.authorNAVARRO, Pablo
dc.contributor.authorHUNEMEIER, Tabita
dc.contributor.authorPEREIRA, Alexandre C.
dc.contributor.authorGONZALEZ-JOSE, Rolando
dc.contributor.authorDELRIEUX, Claudio
dc.date.accessioned2023-11-16T20:09:05Z
dc.date.available2023-11-16T20:09:05Z
dc.date.issued2023
dc.description.abstractSkin health has become a topic of interest in the recent years. To ensure a better diagnosis and treatment, the analysis of high-quality skin databases is crucial. In this regard, UV imaging is a valuable tool in detecting melanoma and other skin conditions. However, UV images present some challenges both in availability and processing. For this reason, in this work we present UVnet, a method to generate opticalto-UV facial images based on autoencoder architectures. The proposed UVnet is validated across an extension of the Baependi Heart Study and other state of the art method [1]. Our proposal successfully generates pseudo-UV samples with an average RMSE of 0.0040 and a structural similarity index against the actual samples of 0.2984. These results show that UVnet consistently achieves higher sample quality than existing methods and provides new capabilities regarding generation of large areas of the facial epidermis. This can be regarded as an initial effort to provide affordable access to high-quality skin databases.eng
dc.description.conferencedateAPR 18-21, 2023
dc.description.conferencelocalCartagena, COLOMBIA
dc.description.conferencename20th IEEE International Symposium on Biomedical Imaging (ISBI)
dc.description.indexPubMed
dc.description.indexWoS
dc.identifier.citation2023 IEEE 20TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING, ISBI, 2023
dc.identifier.doi10.1109/ISBI53787.2023.10230350
dc.identifier.isbn978-1-6654-7358-3
dc.identifier.issn1945-7928
dc.identifier.urihttps://observatorio.fm.usp.br/handle/OPI/57150
dc.language.isoeng
dc.publisherIEEEeng
dc.relation.ispartof2023 Ieee 20th International Symposium on Biomedical Imaging, Isbi
dc.relation.ispartofseriesIEEE International Symposium on Biomedical Imaging
dc.rightsrestrictedAccesseng
dc.rights.holderCopyright IEEEeng
dc.subjectMachine Learningeng
dc.subjectUneteng
dc.subjectUV imagingeng
dc.subjectfacial skineng
dc.subject.wosComputer Science, Artificial Intelligenceeng
dc.subject.wosEngineering, Biomedicaleng
dc.subject.wosRadiology, Nuclear Medicine & Medical Imagingeng
dc.titleDEEP LEARNING BASED UV FACIAL IMAGING GENERATIONeng
dc.typeconferenceObjecteng
dc.type.categoryproceedings papereng
dc.type.versionpublishedVersioneng
dspace.entity.typePublication
hcfmusp.affiliation.countryArgentina
hcfmusp.affiliation.countryisoar
hcfmusp.author.externalMARGALEF, Pablo Toledo:CENPAT, Inst Patagonico Ciencias Soci & Humanas, Puerto Madryn, Argentina; Univ Nacl Patagonia San Juan Bosco, Dept Informatica, Trelew, Argentina; Consejo Nacl Invest Cientificas & Tecnicas CONICE, Buenos Aires, DF, Argentina
hcfmusp.author.externalNAVARRO, Pablo:CENPAT, Inst Patagonico Ciencias Soci & Humanas, Puerto Madryn, Argentina; Univ Nacl Patagonia San Juan Bosco, Dept Informatica, Trelew, Argentina; Consejo Nacl Invest Cientificas & Tecnicas CONICE, Buenos Aires, DF, Argentina
hcfmusp.author.externalHUNEMEIER, Tabita:Univ Sao Paulo, Dept Genet & Biol Evolutiva, Sao Paulo, Brazil
hcfmusp.author.externalGONZALEZ-JOSE, Rolando:CENPAT, Inst Patagonico Ciencias Soci & Humanas, Puerto Madryn, Argentina; Consejo Nacl Invest Cientificas & Tecnicas CONICE, Buenos Aires, DF, Argentina
hcfmusp.author.externalDELRIEUX, Claudio:Consejo Nacl Invest Cientificas & Tecnicas CONICE, Buenos Aires, DF, Argentina; Univ Nacl Sur UNS, Dept Ingn Elect & Computadoras, Bahia Blanca, Buenos Aires, Argentina
hcfmusp.contributor.author-fmusphcALEXANDRE DA COSTA PEREIRA
hcfmusp.origemWOS
hcfmusp.origem.wosWOS:001062050500028
hcfmusp.publisher.cityNEW YORKeng
hcfmusp.publisher.countryUSAeng
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