Detection of Breast Cancer by Thermal Based Sensors using Multilayered Neural Network Classifier

Abstract

Consideration of public health problem issues, one of the most common diseases in public is cancer. Most of the women population is suffering from breast cancer which is the most well known appearance of cancer in metropolitan cities of India and abroad. There many number of imaging modalities to diagnose cancerous cells. Among those, mammography is alone an imaging modality which diagnoses the breast cancer at an early stage. Furthermore, this modality involves X-rays which are more harmful to human health and make the patient inconvenience. Through the mammogram, doctors can analyze, estimate and evaluate the cancer stage so that doctors can give better and correct treatment to the patients. With this mortality and death rates can also be diminished up to some extent. In this paper, the author proposed an intelligent system to identify and find out the severity of breast cancer. By using a thermal based sensor which is of negative Temperature Coefficient (NTC) available with C-MET Thrissur which replaces Mammography. The stage at which the cancer is progressing is classified with the help of Intelligent System Algorithms which works on the temperature data obtained from the thermal device. The data is pre-processed and applied to multilayered backpropogation neural network model. The neural network classifies the preprocessed images into normal, benign and cancer. The output of the network is presented to the doctors through graphs and displays.