Generative fabrication of medical images for machine learning training (2025)
- Authors:
- Autor USP: LEJBMAN, ALFREDO GOLDMAN VEL - IME
- Unidade: IME
- DOI: 10.1109/SBAC-PAD66369.2025.00022
- Subjects: REDES NEURAIS; APRENDIZADO COMPUTACIONAL; PROCESSAMENTO DE IMAGENS; DOENÇA DE ALZHEIMER
- Keywords: Alzheimer's Disease; Binarization; Convolutional Neural Network; Data Augmentation; Generative Adversarial Networks; Histograms
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway
- Date published: 2025
- Source:
- Conference titles: Proceedings
- Status:
- Artigo possui versão em acesso aberto em repositório (Green Open Access)
- Versão do Documento:
- Versão submetida (Pré-print)
- Acessar versão aberta:
-
ABNT
CALZADA-JASSO, Andres G. et al. Generative fabrication of medical images for machine learning training. 2025, Anais.. Piscataway: IEEE, 2025. Disponível em: https://doi.org/10.1109/SBAC-PAD66369.2025.00022. Acesso em: 02 abr. 2026. -
APA
Calzada-Jasso, A. G., Tchernykh, A., Avendaño-Pacheco, I. D., Cortés-Mendoza, J. M., Pulido-Gaytan, B., Babenko, M., et al. (2025). Generative fabrication of medical images for machine learning training. In International Symposium on Computer Architecture and High Performance Computing - SBAC-PAD. Piscataway: IEEE. doi:10.1109/SBAC-PAD66369.2025.00022 -
NLM
Calzada-Jasso AG, Tchernykh A, Avendaño-Pacheco ID, Cortés-Mendoza JM, Pulido-Gaytan B, Babenko M, Goldman A, González-Vélez H. Generative fabrication of medical images for machine learning training [Internet]. International Symposium on Computer Architecture and High Performance Computing - SBAC-PAD. 2025 ;[citado 2026 abr. 02 ] Available from: https://doi.org/10.1109/SBAC-PAD66369.2025.00022 -
Vancouver
Calzada-Jasso AG, Tchernykh A, Avendaño-Pacheco ID, Cortés-Mendoza JM, Pulido-Gaytan B, Babenko M, Goldman A, González-Vélez H. Generative fabrication of medical images for machine learning training [Internet]. International Symposium on Computer Architecture and High Performance Computing - SBAC-PAD. 2025 ;[citado 2026 abr. 02 ] Available from: https://doi.org/10.1109/SBAC-PAD66369.2025.00022 - The influence of organizational factors on inter-team knowledge sharing effectiveness in agile environments
- Improving the performance of actor model runtime environments on multicore and manycore platforms
- Towards automatic actor pinning on multi-core architectures
- A simple BSP-based model to predict execution time in GPU applications
- A comparison of GPU execution time prediction using machine learning and analytical modeling
- Message from the program committee co-chairs. [Apresentação]
- Useful statistical methods for human factors research in software engineering: a discussion on validation with quantitative data
- Trying to increase the mature use of agile practices by Group Development Psychology Training: an experiment
- Scheduling moldable BSP tasks on clouds
- A multithreaded resolution of the service selection problem based on domain decomposition and work stealing
Informações sobre a disponibilidade de versões do artigo em acesso aberto coletadas automaticamente via oaDOI API (Unpaywall).
Por se tratar de integração com serviço externo, podem existir diferentes versões do trabalho (como preprints ou postprints), que podem diferir da versão publicada.
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
| 3281583_-_Generative_fabr... |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
