Breast cancer detection by fusion of deep features with CNN extracted features
Liang Zhou, Amita Nandal, Todor Dimitrov Ganchev, Arvind Dhaka · International Journal of Intelligent Systems Technologies and Applications · 2022
Breast cancer growth has become a typical factor nowadays. Physician experience of diagnosing and detecting breast cancer can be assisted by using some computerised features extraction and classification algorithms. In the recent times, breast cancer can be diagnosed by classifying tumours. In this paper, breast cancer identification and analysis is done by using machine learning statistical analysis. The proposed technique has proven to improve the exactness of foreseeing predicting cancer. The proposed method used optimised recording condition of the input image and later introduces a new interpretable feature for the identification. The simulation results are compared with conventional methods by using accuracy, sensitivity and specificity for performance assessment of the identification process.