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ubuk x Abstract: The advances in image processing technology contribute to the inter- pretation of medical images and early diagnosis. Moreover various studies can be found in medical journals dedicated to Artificial Neural Networks (ANN). In the presented study, a method was developed to learn and detect benign and malig- nant tumor types in contrast-enhanced breast magnetic resonance images (MRI). The backpropagation algorithm was taken as the ANN learning algorithm. The algorithm (NEUBREA) was developed in C# programming language by using Fast Artificial Neural Network Library (FANN). Having been diagnosed by radiologists, 7 cases of malignant tumor, 8 cases of benign tumor, and 3 normal cases were used as a training set. The results were tested on 34 cases that had been diagnosed by radiologists. After the comparison of the results, the overall accuracy of algorithm was defined as 92%.

AN EFFICIENT ALGORITHM FOR AUTOMATIC TUMOR DETECTION IN CONTRAST ENHANCED BREAST MRI BY USING ARTIFICIAL NEURAL NETWORK (NEUBREA)