Abstract— Breast cancer presents a serious medical and social problem worldwide. Early detection is a key to effective breast cancer treatment. Electrical Impedance Tomography (EIT) is a medical imaging technique that reconstructs internal electrical conductivity distribution of a body from impedance data, which can be used for detection of breast cancer. In this paper publicly available data of breast cancer is used to design and optimized Radial Basis Function (RBF) Neural Network based Classifier. Classifier is tested for generalization, which proves as an elegant classifier with the accuracy of 93%.
Index Terms— Breast cancer, electrical impedance, RBF
P. C. Shetiye, is with Government College of Engineering Karad, Maharashtra, 415124, India (e-mail: praveen.shetiye@gmail.com).
A. A. Ghatol was with Dr. B. A. T. U. Lonere, India (e-mail: aaghatol@gmail.com).
V. N. Ghate and S. R. Patil are with Government College of Engineering Chandrapur, Maharashtra, 442403, India (e-mail: vng786@gmail.com, sanjaypatil_71@yahoo.com ).
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Cite: P. C. Shetiye, A. A. Ghatol, V. N. Ghate, and S. R. Patil, " Detection of Breast Cancer Using Electrical Impedance and RBF Neural Network," International Journal of Information and Electronics Engineering vol. 5, no. 5, pp. 356-360, 2015.
