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- Vol. 6 Issue 2
- Article
Automated Breast Cancer Detection Using Ultrasound Images and Deep Learning
Authors
1 Assistant Professor Department of Information Technology Er. Perumal Manimekalai College of Engineering Hosur, Tamil Nadu, India. 2 3 4 5 Department of Information Technology Er. Perumal Manimekalai College of Engineering Hosur, Tamil Nadu, India.
Article Information
- Published In
- Volume 6, Issue 2 (2026)
- Published Online
- March-April 2026
- Pages
- 416-420
- Article Type
- Original Article
References
1. A. Krizhevsky et al., “ImageNet Classification with Deep CNN,” IEEE, 2012.
2. S. Litjens et al., “Deep Learning in Medical Image Analysis,” 2017.
3. WHO, “Breast Cancer Report,” 2023.
4. Goodfellow et al., Deep Learning, MIT Press, 2016.
5. BUSI Dataset: Breast Ultrasound Images Dataset.
6. H. Fujita, “AI-based Computer-Aided Diagnosis (CAD): Current Status and Future Prospects in Medical Imaging,”
Radiological Physics and Technology, vol. 13, no. 1, pp. 1–10, 2020.
7. M. Byra et al., “Breast Mass Classification in Ultrasound Images Using Deep Convolutional Neural Networks,” Biomedical
Signal Processing and Control, vol. 45, pp. 287–296, 2018.
8. D. Shen, G. Wu, and H. Suk, “Deep Learning in Medical Image Analysis,” Annual Review of Biomedical Engineering, vol.
19, pp. 221–248, 2017.
9. K. Simonyan and A. Zisserman, “Very Deep Convolutional Networks for Large-Scale Image Recognition,” International
Conference on Learning Representations (ICLR), 2015.
10. K. He, X. Zhang, S. Ren, and J. Sun, “Deep Residual Learning for Image Recognition,” IEEE Conference on Computer
Vision and Pattern Recognition (CVPR), 2016.
11. M. Tan and Q. Le, “EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks,” International Conference
on Machine Learning (ICML), 2019.
12. R. Srivastava et al., “Breast Cancer Detection Using Deep Learning: A Review,” International Journal of Engineering
Research & Technology, 2020.
13. A. Yap et al., “Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks,” IEEE Journal of
Biomedical and Health Informatics, 2018.
14. S. Minaee et al., “Image Segmentation Using Deep Learning: A Survey,” IEEE Transactions on Pattern Analysis and
Machine Intelligence, 2021.
15. WHO, “Breast Cancer Facts and Statistics,” World Health Organization, 2023
2. S. Litjens et al., “Deep Learning in Medical Image Analysis,” 2017.
3. WHO, “Breast Cancer Report,” 2023.
4. Goodfellow et al., Deep Learning, MIT Press, 2016.
5. BUSI Dataset: Breast Ultrasound Images Dataset.
6. H. Fujita, “AI-based Computer-Aided Diagnosis (CAD): Current Status and Future Prospects in Medical Imaging,”
Radiological Physics and Technology, vol. 13, no. 1, pp. 1–10, 2020.
7. M. Byra et al., “Breast Mass Classification in Ultrasound Images Using Deep Convolutional Neural Networks,” Biomedical
Signal Processing and Control, vol. 45, pp. 287–296, 2018.
8. D. Shen, G. Wu, and H. Suk, “Deep Learning in Medical Image Analysis,” Annual Review of Biomedical Engineering, vol.
19, pp. 221–248, 2017.
9. K. Simonyan and A. Zisserman, “Very Deep Convolutional Networks for Large-Scale Image Recognition,” International
Conference on Learning Representations (ICLR), 2015.
10. K. He, X. Zhang, S. Ren, and J. Sun, “Deep Residual Learning for Image Recognition,” IEEE Conference on Computer
Vision and Pattern Recognition (CVPR), 2016.
11. M. Tan and Q. Le, “EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks,” International Conference
on Machine Learning (ICML), 2019.
12. R. Srivastava et al., “Breast Cancer Detection Using Deep Learning: A Review,” International Journal of Engineering
Research & Technology, 2020.
13. A. Yap et al., “Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks,” IEEE Journal of
Biomedical and Health Informatics, 2018.
14. S. Minaee et al., “Image Segmentation Using Deep Learning: A Survey,” IEEE Transactions on Pattern Analysis and
Machine Intelligence, 2021.
15. WHO, “Breast Cancer Facts and Statistics,” World Health Organization, 2023
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