SuGAR: a framework to support mammogram diagnosis (2007)
- Authors:
- USP affiliated authors: TRAINA, AGMA JUCI MACHADO - ICMC ; TRAINA JUNIOR, CAETANO - ICMC ; MARQUES, PAULO MAZZONCINI DE AZEVEDO - FMRP
- Unidades: ICMC; FMRP
- Subjects: COMPUTAÇÃO GRÁFICA; PROCESSAMENTO DE IMAGENS; BANCO DE DADOS
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Los Alamitos
- Date published: 2007
- ISBN: 10637125
- Source:
- Título: Proceedings
- Conference titles: IEEE International Symposium on Computer-Based Medical Systems
-
ABNT
RIBEIRO, Marcela Xavier et al. SuGAR: a framework to support mammogram diagnosis. 2007, Anais.. Los Alamitos: IEEE, 2007. . Acesso em: 05 nov. 2024. -
APA
Ribeiro, M. X., Traina, A. J. M., Balan, A. G. R., Traina Junior, C., & Marques, P. M. de A. (2007). SuGAR: a framework to support mammogram diagnosis. In Proceedings. Los Alamitos: IEEE. -
NLM
Ribeiro MX, Traina AJM, Balan AGR, Traina Junior C, Marques PM de A. SuGAR: a framework to support mammogram diagnosis. Proceedings. 2007 ;[citado 2024 nov. 05 ] -
Vancouver
Ribeiro MX, Traina AJM, Balan AGR, Traina Junior C, Marques PM de A. SuGAR: a framework to support mammogram diagnosis. Proceedings. 2007 ;[citado 2024 nov. 05 ] - Content-based retrieval of medical images: from context to perception
- Reducing the semantic gap in content-based image retrieval in mammography with relevance feedback and inclusion of expert knowledge
- The metric histogram: a new and efficient approach for content-based image retrieval
- Recuperação de imagem baseada em conteúdo: uso de atributos de textura para caracterização de microcalcificações mamográficas
- Issues and techniques to mitigate the performance gap in content-based image retrieval systems
- The 28th IEEE International Symposium on... [Prefácio]
- Integrando textura e forma para a recuperação de imagens por conteúdo
- Smart histogram analysis applied to the skull-stripping problem in T1-weighted MRI
- How to add content-based image retrieval capability in a PACS
- How to improve medical image diagnosis through association rules: the IDEA method
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