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The study done in this paper focuses on the detection of breast cancer by neuronal approach, by rotating the transmitting antenna from 15◦, 30◦, 45◦, 60◦, 75◦, to 90◦ relative to its initial position which is of 0◦ (i.e., to the opposite of the receiving antenna). We have generated our database by using a CST electromagnetic simulator for each antenna location. Then the learning and test phases of our artificial neural network (ANN) are done for seven antennae locations using two learning algorithms which are: the Scaled Conjugate Gradient Back-propagation (Trainscg) and the Gradient Descent with Momentum (Traingdm). A comparative study was conducted for all the seven cases. The results obtained are very satisfying and show that the best location of the transmitter antenna is at 60◦ and that the learning algorithm Trainscg gives better results than Traingdm.

A COMPARATIVE STUDY FOR BREAST CANCER DETECTION BY NEURAL APPROACH FOR DIFFERENT CONFIGURATIONS OF THE MICROWAVE IMAGING SYSTEM