Breast Cancer Classification from Ultrasound Images Using Probability-Based Optimal Deep Learning Feature Fusion
HITEC University · University of Ha'il · +3 more institutions
Abstract
After lung cancer, breast cancer is the second leading cause of death in women. If breast cancer is detected early, mortality rates in women can be reduced. Because manual breast cancer diagnosis takes a long time, an automated system is required for early cancer detection. This paper proposes a new framework for breast cancer classification from ultrasound images that employs deep learning and the fusion of the best selected features. The proposed framework is divided into five major steps: (i) data augmentation is performed to increase the size of the original dataset for better learning of Convolutional Neural Network (CNN) models; (ii) a pre-trained DarkNet-53 model is considered and the output layer is…
Citation impact
- FWCI
- 36.90
- Percentile
- 100%
- References
- 67
Authors
8- KJKiran Jabeen
HITEC University
- MAMuhammad Attique Khan
HITEC University
- MAMajed Alhaisoni
University of Ha'il
- UTUsman Tariq
Prince Sattam Bin Abdulaziz University
- YZYudong Zhang
University of Leicester
Topics & keywords
- Artificial intelligence
- Computer science
- Breast cancer
- Deep learning
- Convolutional neural network
- Transfer of learning
- Pooling
- Machine learning
- Good health and well-being