Segmenting skin ulcers and measuring the wound area using deep convolutional networks (2020)
- Authors:
- USP affiliated authors: TRAINA JUNIOR, CAETANO - ICMC ; TRAINA, AGMA JUCI MACHADO - ICMC ; CHINO, DANIEL YOSHINOBU TAKADA - ICMC ; SCABORA, LUCAS DE CARVALHO - ICMC ; CAZZOLATO, MIRELA TEIXEIRA - ICMC
- Unidade: ICMC
- DOI: 10.1016/j.cmpb.2020.105376
- Subjects: PROCESSAMENTO DE IMAGENS; RECONHECIMENTO DE IMAGEM; REDES NEURAIS; ÚLCERA CUTÂNEA; TECNOLOGIAS DA SAÚDE
- Keywords: Skin ulcer; Image segmentation; Deep convolutional neural networks; Wound measurement
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Computer Methods and Programs in Biomedicine
- ISSN: 0169-2607
- Volume/Número/Paginação/Ano: v. 191, p. 1-11, July 2020
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: hybrid
- Licença: unspecified-oa
-
ABNT
CHINO, Daniel Yoshinobu Takada et al. Segmenting skin ulcers and measuring the wound area using deep convolutional networks. Computer Methods and Programs in Biomedicine, v. 191, p. 1-11, 2020Tradução . . Disponível em: https://doi.org/10.1016/j.cmpb.2020.105376. Acesso em: 27 dez. 2025. -
APA
Chino, D. Y. T., Scabora, L. de C., Cazzolato, M. T., Jorge, A. E. S., Traina Junior, C., & Traina, A. J. M. (2020). Segmenting skin ulcers and measuring the wound area using deep convolutional networks. Computer Methods and Programs in Biomedicine, 191, 1-11. doi:10.1016/j.cmpb.2020.105376 -
NLM
Chino DYT, Scabora L de C, Cazzolato MT, Jorge AES, Traina Junior C, Traina AJM. Segmenting skin ulcers and measuring the wound area using deep convolutional networks [Internet]. Computer Methods and Programs in Biomedicine. 2020 ; 191 1-11.[citado 2025 dez. 27 ] Available from: https://doi.org/10.1016/j.cmpb.2020.105376 -
Vancouver
Chino DYT, Scabora L de C, Cazzolato MT, Jorge AES, Traina Junior C, Traina AJM. Segmenting skin ulcers and measuring the wound area using deep convolutional networks [Internet]. Computer Methods and Programs in Biomedicine. 2020 ; 191 1-11.[citado 2025 dez. 27 ] Available from: https://doi.org/10.1016/j.cmpb.2020.105376 - Efficient indexing of multiple metric spaces with spectra
- Semi-automatic ulcer segmentation and wound area measurement supporting telemedicine
- Exploratory data analysis in electronic health records graphs: intuitive features and visualization tools
- UCORM: indexing uncorrelated metric spaces for concise content-based retrieval of medical images
- FeatSet: a compilation of visual features extracted from public image datasets
- FeatSet+: visual features extracted from public image datasets
- SHARq: sharing recursive queries in relational databases
- VD-Tree: how to build an efficient and fit metric access method using Voronoi diagrams
- Establishing trajectories of moving objects without identities: the intricacies of cell tracking and a solution
- Combining semantic graph features and a common data model to exploit the interoperability of patient databases
Informações sobre o DOI: 10.1016/j.cmpb.2020.105376 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
2989091.pdf | ||
 |
2989091_post.pdf | Direct link |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
