Using Stochastic Techniques to Detect Breast Cancer in Infrared Thermographies

Abstract

Thermo graphical infrared images to predict the existence of a thermal anomaly according to symmetry in breasts by using stochastic methods and fuzzy logic control is proposed. Statistical results are established through entropy, kurtosis and media to evaluate symmetry grade between right and left breast. To predict the grade of breast cancer associated to the tissue and take a decision a fuzzy controller is designed in base to symmetric assessments distribution. The proposed method is implemented on a FPGA platform optimizing hardware requirements and improves response time. Results show that the error of the prediction method can be an alternative to detect cancer if the images source are far away from the critical errors, interference to the source or infrared image processed.