Type:	Monografia
Título :	Applications of deep learning to measure skin lesions
Author:	Penha, Cecília de Oliveira
First advisor:	Feitosa, Samuel da Silva
metadata.dc.contributor.advisor-co1:	Lima, Julyane Felipette
Resume:	When 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.
Palabras clave :	Aprendizagem profunda Inteligência artificial Doenças da pele e do tecido conjuntivo Ferimentos e lesões Processamento de imagens
Language:	por
Country:	Brasil
Editorial :	Universidade Federal da Fronteira Sul
Acronym of the institution:	UFFS
College, Institute or Department:	Campus Chapecó
Type of Access:	Acesso Aberto
URI :	https://rd.uffs.edu.br/handle/prefix/9168
Fecha de publicación :	2025
Aparece en las colecciones:	Ciência da Computação

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