Transfer learning in deep convolutional neural networks for detection of architectural distortion in digital mammography (2020)
- Authors:
- USP affiliated authors: VIEIRA, MARCELO ANDRADE DA COSTA - EESC ; COSTA, ARTHUR CHAVES - EESC ; BORGES, LUCAS RODRIGUES - FMRP
- Unidades: EESC; FMRP
- DOI: 10.1117/12.2564348
- Subjects: MAMOGRAFIA; APRENDIZAGEM PROFUNDA; REDES NEURAIS
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher place: Washington, DC
- Date published: 2020
- Source:
- Título: Proceedings of the SPIE
- ISSN: 0277-786X
- Volume/Número/Paginação/Ano: v. 11513
- Conference titles: International Workshop on Breast Imaging - IWBI
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
COSTA, Arthur C. et al. Transfer learning in deep convolutional neural networks for detection of architectural distortion in digital mammography. Proceedings of the SPIE. Washington, DC: Escola de Engenharia de São Carlos, Universidade de São Paulo. Disponível em: http://dx.doi.org/10.1117/12.2564348. Acesso em: 28 fev. 2026. , 2020 -
APA
Costa, A. C., Oliveira, H. C. R., Borges, L. R., & Vieira, M. A. da C. (2020). Transfer learning in deep convolutional neural networks for detection of architectural distortion in digital mammography. Proceedings of the SPIE. Washington, DC: Escola de Engenharia de São Carlos, Universidade de São Paulo. doi:10.1117/12.2564348 -
NLM
Costa AC, Oliveira HCR, Borges LR, Vieira MA da C. Transfer learning in deep convolutional neural networks for detection of architectural distortion in digital mammography [Internet]. Proceedings of the SPIE. 2020 ; 11513[citado 2026 fev. 28 ] Available from: http://dx.doi.org/10.1117/12.2564348 -
Vancouver
Costa AC, Oliveira HCR, Borges LR, Vieira MA da C. Transfer learning in deep convolutional neural networks for detection of architectural distortion in digital mammography [Internet]. Proceedings of the SPIE. 2020 ; 11513[citado 2026 fev. 28 ] Available from: http://dx.doi.org/10.1117/12.2564348 - Analysis of feature relevance using an image quality index applied to digital mammography
- Noise models for virtual clinical trials of digital breast tomosynthesis
- Unbiased injection of signal-dependent noise in variance-stabilized range
- Data augmentation: effect in deep convolutional neural network for the detection of architectural distortion in digital mammography
- Noise modeling and variance stabilization of a computed radiography (CR) mammography system subject to fixed-pattern noise
- Denoising of mammograms subject to structural and spatially-correlated noise: a virtual clinical trial
- Effect of denoising on the localization of microcalcification clusters in digital mammography
- Open-source reconstruction toolbox for digital breast tomosynthesis
- Detecção de distorção arquitetural mamária em mamografia digital utilizando rede neural convolucional profunda
- Digital breast tomosynthesis: new strategies for optimizing acquisition geometry
Informações sobre o DOI: 10.1117/12.2564348 (Fonte: oaDOI API)
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