A Detailed Survey of Textural Features in Breast Cancer Detection Using Deep Learning

Early cancer diagnosis is crucial for effective health management. This paper explores various approaches for the early prognostication of breast cancer. We focus on applying textural features and Convolutional Neural Networks (CNNs) to develop a model distinguishing between normal and abnormal classes. Furthermore, the model identifies and differentiates benign tumours from malignant ones within the abnormal cases. Textural features present a viable option for early diagnosis due to their fast computational capabilities and cancer staging.