Novel Segmentation Method to Diagnose Breast Cancer in Thermography Using Deep Convolutional Neural Network

Abstract

Based on the recent analysis it is more evident that in Indiabreast cancer has become the most common type of cancer among women. There is an increase in the number of patients suffering from breast cancer especially in rural areas. Another fact is the patients with young age groups are increasing more when compared earlier. The only remedy is prior detection leading to more survival rate. Research is in progress for latest diagnosis method employing machine learning and deep learning techniques. One such deep learning method discussed in this paper is the convolutional neural network model used for thermal image segmentation. Spatial pyramid pooling method is combined with modified U-Net Architecture to give accurate results. Thermography images are used for diagnosis which is more innovative compared with other screening methods. Using the proposed method, the segmented images when tested for classification produces an accuracy of 96.13% trained with Residual network model with loss of 0.40%.