Deep learning for automatic segmentation of clinical photographs of oral premalignant and malignant lesions (2023)
- Authors:
- USP affiliated authors: CARVALHO, ANDRÉ CARLOS PONCE DE LEON FERREIRA DE - ICMC ; SOUZA, EDUARDO SANTOS CARLOS DE - ICMC
- Unidade: ICMC
- DOI: 10.1016/j.oooo.2023.03.068
- Subjects: APRENDIZAGEM PROFUNDA; RECONHECIMENTO DE IMAGEM; NEOPLASIAS BUCAIS; NEOPLASIAS DE CABEÇA E PESCOÇO; TECNOLOGIAS DA SAÚDE
- Language: Inglês
- Imprenta:
- Source:
- Título: Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology
- ISSN: 2212-4403
- Volume/Número/Paginação/Ano: v. 136, n. 1, p. e31-e32, July 2023
- Conference titles: Brazilian Congress of Stomatology and Oral Pathology
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
ARAUJO, Anna Luiza Damaceno et al. Deep learning for automatic segmentation of clinical photographs of oral premalignant and malignant lesions. Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology. New York: Elsevier. Disponível em: https://doi.org/10.1016/j.oooo.2023.03.068. Acesso em: 03 jan. 2026. , 2023 -
APA
Araujo, A. L. D., Souza, E. S. C. de, Faustino, I. S. P., Saldivia-Siracusa, C., Lopes, M. A., Carvalho, A. C. P. de L. F. de, & Santos-Silva, A. R. dos. (2023). Deep learning for automatic segmentation of clinical photographs of oral premalignant and malignant lesions. Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology. New York: Elsevier. doi:10.1016/j.oooo.2023.03.068 -
NLM
Araujo ALD, Souza ESC de, Faustino ISP, Saldivia-Siracusa C, Lopes MA, Carvalho ACP de LF de, Santos-Silva AR dos. Deep learning for automatic segmentation of clinical photographs of oral premalignant and malignant lesions [Internet]. Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology. 2023 ; 136( 1): e31-e32.[citado 2026 jan. 03 ] Available from: https://doi.org/10.1016/j.oooo.2023.03.068 -
Vancouver
Araujo ALD, Souza ESC de, Faustino ISP, Saldivia-Siracusa C, Lopes MA, Carvalho ACP de LF de, Santos-Silva AR dos. Deep learning for automatic segmentation of clinical photographs of oral premalignant and malignant lesions [Internet]. Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology. 2023 ; 136( 1): e31-e32.[citado 2026 jan. 03 ] Available from: https://doi.org/10.1016/j.oooo.2023.03.068 - Machine learning concepts applied to oral pathology and oral medicine: a convolutional neural networks' approach
- Segmentation of oral lesions through convolutional neural networks
- A convolutional neural network framework with ConvNeXt and Grad-CAM for classification of oral potentially malignant disorders and oral squamous cell carcinoma
- Enhancing explainability in oral cancer detection with Grad-CAM visualizations
- Convnext for the classification of oral potentially malignant disorders and squamous cell carcinoma
- Automated classification of oral potentially malignant disorders and oral squamous cell carcinoma using a convolutional neural network framework: a cross-sectional study
- Clinicians' perception of oral potentially malignant disorders: a pitfall for image annotation in supervised learning
- Reduction strategies for hierarchical multi-label classification in protein function prediction
- Intelligent-guided adaptive search for the maximum covering location problem
- Clus-DTI: improving decision-tree classification with a clustering-based decision-tree induction algorithm
Informações sobre o DOI: 10.1016/j.oooo.2023.03.068 (Fonte: oaDOI API)
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