This repository was created for the research paper "Attention-Based Deep Learning Approach for Breast Cancer Histopathological Images Multi-Classification."

Dataset

The dataset used in this study is BreakHis. It is accessible at the Breast Cancer Histopathological Database.

References

• F. A. Spanhol, L. S. Oliveira, C. Petitjean, and L. Heutte, "A Dataset for Breast Cancer Histopathological Image Classification," IEEE Transactions on Biomedical Engineering, vol. 63, no. 7, pp. 1455-1462, 2016. [DOI: 10.1109/TBME.2015.2496264.
• M. Tan and Q. V. Le, "EfficientNetV2: Smaller models and faster training," arXiv preprint arXiv:2104.00298, 2021, DOI: 10.48550/arXiv.2104.00298.
• D. Hendrycks et al., "AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty," arXiv preprint arXiv:1912.02781, Feb. 2020, DOI: 10.48550/arXiv.1912.02781.
• Woo S, Park J, Lee J Y, et al. CBAM: Convolutional Block Attention Module[J]. 2018. ECCV2018
• Luuuyi, "luuuyi/CBAM.PyTorch: Non-official implement of Paper：CBAM: Convolutional Block Attention Module," GitHub repository, Accessed on (2024-04-04). URL
• J. Gildenblat and contributors, "PyTorch library for CAM methods," GitHub repository, Accessed on (2024-04-07).URL