Convolutional Neural Networks in Breast Cancer Diagnosis: An Integrated Model
Dafnee, M. Jayasheela · 2024
Breast cancer is always the top most reason for the increase in death rate of women. Therefore advancements in diagnosing technique is very much needed, so that the breast cancer can be detected without false positives or false negatives for clinicians to take necessary action at the earlier stage. Deep learning technique like Convolutional Neural Networks (CNNs) has become a very successful tool in medical imaging specifically for breast cancer diagnosis. Imaging modalities like mammogram, ultrasound and MRI has become the primary source of breast cancer diagnosis. This paper proposed the idea of integrating multiple CNN architectures with mammogram datasets for training the model and make use of ensemble technique to detect the breast cancer during the testing phase. This Integrated CNN model is expected to achieve higher detection accuracy with less false positive rate.