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Artigo de periodico
The UTrack framework for segmenting and measuring dermatological ulcers through telemedicine (2021)
Cazzolato, Mirela Teixeira ; Ramos, Jonathan da Silva ; Rodrigues, Lucas Santiago ; Scabora, Lucas de Carvalho ; Chino, Daniel Yoshinobu Takada ; Jorge, Ana Elisa Serafim ; Azevedo-Marques, Paulo Mazzoncini de ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Computers in Biology and Medicine. Unidades: FMRP, ICMC
Subjects: PROCESSAMENTO DE IMAGENS, RECONHECIMENTO DE IMAGEM, TECNOLOGIAS DA SAÚDE, TELEMEDICINA, ÚLCERA CUTÂNEA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAZZOLATO, Mirela Teixeira et al. The UTrack framework for segmenting and measuring dermatological ulcers through telemedicine. Computers in Biology and Medicine, v. 134, p. 1-17, 2021Tradução . . Disponível em: https://doi.org/10.1016/j.compbiomed.2021.104489. Acesso em: 14 set. 2024.
APA
Cazzolato, M. T., Ramos, J. da S., Rodrigues, L. S., Scabora, L. de C., Chino, D. Y. T., Jorge, A. E. S., et al. (2021). The UTrack framework for segmenting and measuring dermatological ulcers through telemedicine. Computers in Biology and Medicine, 134, 1-17. doi:10.1016/j.compbiomed.2021.104489
NLM
Cazzolato MT, Ramos J da S, Rodrigues LS, Scabora L de C, Chino DYT, Jorge AES, Azevedo-Marques PM de, Traina Junior C, Traina AJM. The UTrack framework for segmenting and measuring dermatological ulcers through telemedicine [Internet]. Computers in Biology and Medicine. 2021 ; 134 1-17.[citado 2024 set. 14 ] Available from: https://doi.org/10.1016/j.compbiomed.2021.104489
Vancouver
Cazzolato MT, Ramos J da S, Rodrigues LS, Scabora L de C, Chino DYT, Jorge AES, Azevedo-Marques PM de, Traina Junior C, Traina AJM. The UTrack framework for segmenting and measuring dermatological ulcers through telemedicine [Internet]. Computers in Biology and Medicine. 2021 ; 134 1-17.[citado 2024 set. 14 ] Available from: https://doi.org/10.1016/j.compbiomed.2021.104489
Artigo de periodico
A superpixel-driven deep learning approach for the analysis of dermatological wounds (2020)
Blanco, Gustavo; Traina, Agma Juci Machado ; Traina Junior, Caetano ; Azevedo-Marques, Paulo Mazzoncini de ; Jorge, Ana Elisa Serafim ; Oliveira, Daniel de; Bêdo, Marcos Vinícius Naves
Source: Computer Methods and Programs in Biomedicine. Unidades: ICMC, FMRP
Subjects: PROCESSAMENTO DE IMAGENS, APRENDIZADO COMPUTACIONAL, RECONHECIMENTO DE IMAGEM, ÚLCERA CUTÂNEA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
BLANCO, Gustavo et al. A superpixel-driven deep learning approach for the analysis of dermatological wounds. Computer Methods and Programs in Biomedicine, v. 183, n. Ja 2020, p. 1-9, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.cmpb.2019.105079. Acesso em: 14 set. 2024.
APA
Blanco, G., Traina, A. J. M., Traina Junior, C., Azevedo-Marques, P. M. de, Jorge, A. E. S., Oliveira, D. de, & Bêdo, M. V. N. (2020). A superpixel-driven deep learning approach for the analysis of dermatological wounds. Computer Methods and Programs in Biomedicine, 183( Ja 2020), 1-9. doi:10.1016/j.cmpb.2019.105079
NLM
Blanco G, Traina AJM, Traina Junior C, Azevedo-Marques PM de, Jorge AES, Oliveira D de, Bêdo MVN. A superpixel-driven deep learning approach for the analysis of dermatological wounds [Internet]. Computer Methods and Programs in Biomedicine. 2020 ; 183( Ja 2020): 1-9.[citado 2024 set. 14 ] Available from: https://doi.org/10.1016/j.cmpb.2019.105079
Vancouver
Blanco G, Traina AJM, Traina Junior C, Azevedo-Marques PM de, Jorge AES, Oliveira D de, Bêdo MVN. A superpixel-driven deep learning approach for the analysis of dermatological wounds [Internet]. Computer Methods and Programs in Biomedicine. 2020 ; 183( Ja 2020): 1-9.[citado 2024 set. 14 ] Available from: https://doi.org/10.1016/j.cmpb.2019.105079
Trabalho de evento
Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine (2020)
Cazzolato, Mirela Teixeira ; Ramos, Jonathan da Silva ; Rodrigues, Lucas Santiago ; Scabora, Lucas de Carvalho ; Chino, Daniel Yoshinobu Takada ; Jorge, Ana Elisa Serafim ; Azevedo-Marques, Paulo Mazzoncini de ; Traina Junior, Caetano ; Traina, Agma Juci Machado
Source: Proceedings. Conference titles: IEEE International Symposium on Computer-Based Medical Systems - CBMS. Unidades: FMRP, ICMC
Subjects: COMPUTAÇÃO MÓVEL, PROCESSAMENTO DE IMAGENS, ÚLCERA CUTÂNEA, TECNOLOGIAS DA SAÚDE, TELEMEDICINA
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
ABNT
CAZZOLATO, Mirela Teixeira et al. Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine. 2020, Anais.. Los Alamitos: IEEE, 2020. Disponível em: https://doi.org/10.1109/CBMS49503.2020.00073. Acesso em: 14 set. 2024.
APA
Cazzolato, M. T., Ramos, J. da S., Rodrigues, L. S., Scabora, L. de C., Chino, D. Y. T., Jorge, A. E. S., et al. (2020). Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine. In Proceedings. Los Alamitos: IEEE. doi:10.1109/CBMS49503.2020.00073
NLM
Cazzolato MT, Ramos J da S, Rodrigues LS, Scabora L de C, Chino DYT, Jorge AES, Azevedo-Marques PM de, Traina Junior C, Traina AJM. Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine [Internet]. Proceedings. 2020 ;[citado 2024 set. 14 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00073
Vancouver
Cazzolato MT, Ramos J da S, Rodrigues LS, Scabora L de C, Chino DYT, Jorge AES, Azevedo-Marques PM de, Traina Junior C, Traina AJM. Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine [Internet]. Proceedings. 2020 ;[citado 2024 set. 14 ] Available from: https://doi.org/10.1109/CBMS49503.2020.00073

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