Please use this identifier to cite or link to this item: https://rd.uffs.edu.br/handle/prefix/9168
Full metadata record
DC FieldValueLanguage
dc.contributor.advisor1Feitosa, Samuel da Silva-
dc.contributor.advisor-co1Lima, Julyane Felipette-
dc.creatorPenha, Cecília de Oliveira-
dc.date2025-12-11-
dc.date.accessioned2026-03-25T13:18:09Z-
dc.date.available2026-
dc.date.available2026-03-25T13:18:09Z-
dc.date.issued2025-
dc.identifier.urihttps://rd.uffs.edu.br/handle/prefix/9168-
dc.description.resumoWhen treating skin lesions, accurate assessment of wound healing re- mains a challenge for health professionals. Precise estimation of the wound area is required to determine if the current approach is efficient or if a new interven- tion is required. This paper proposes a study on the ability of computer vision algorithms and deep learning networks to measure the size of dermatological wounds based on images. By employing an approach based on the U-Net archi- tecture, the study evaluates the model’s ability to segment wounds and provide area estimations. Results demonstrate that the proposed method can support decision making by health professionals by offering consistent measurements, contributing to faster and efficient patient care.pt_BR
dc.description.provenanceSubmitted by Biblioteca Chapeco (biblio.ch@uffs.edu.br) on 2026-03-24T15:55:37Z No. of bitstreams: 1 PENHA.pdf: 1373475 bytes, checksum: b31b6438b677ede8b3087ad3b8816c15 (MD5)en
dc.description.provenanceApproved for entry into archive by DIONE ROSSI FARIAS (dione@uffs.edu.br) on 2026-03-25T13:18:09Z (GMT) No. of bitstreams: 1 PENHA.pdf: 1373475 bytes, checksum: b31b6438b677ede8b3087ad3b8816c15 (MD5)en
dc.description.provenanceMade available in DSpace on 2026-03-25T13:18:09Z (GMT). No. of bitstreams: 1 PENHA.pdf: 1373475 bytes, checksum: b31b6438b677ede8b3087ad3b8816c15 (MD5) Previous issue date: 2025en
dc.languageporpt_BR
dc.publisherUniversidade Federal da Fronteira Sulpt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentCampus Chapecópt_BR
dc.publisher.initialsUFFSpt_BR
dc.rightsAcesso Abertopt_BR
dc.subjectAprendizagem profundapt_BR
dc.subjectInteligência artificialpt_BR
dc.subjectDoenças da pele e do tecido conjuntivopt_BR
dc.subjectFerimentos e lesõespt_BR
dc.subjectProcessamento de imagenspt_BR
dc.titleApplications of deep learning to measure skin lesionspt_BR
dc.typeMonografiapt_BR
Appears in Collections:Ciência da Computação

Files in This Item:
File Description SizeFormat 
PENHA.pdf1.34 MBAdobe PDFView/Open
Show simple item record Recommend this item


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.