Accuracy and interpretability are two important objectives in the design of Adaptive Neuro Fuzzy Inference model (ANFIS). In many real word applications, expert experiences usually have good interpretability, but their accuracy is not always the best. Applying expert experiences to ANFIS model can improve accuracy and interpretability. In this study we propose an accessible tool that helps medical interpretation of suspect zones in MRI. This paper describes ANFIS model combined the neural network adaptive capabilities and the fuzzy logic qualitative approach. Some conclusions concerning the impacts of features on the detection of breast cancer were obtained through analysis of the ANFIS. The use ANFIS improves the diagnostic efficiency in tumor progression. Some of the images show feasibility of the propose methodology. The same is then implemented on DSP TMS320C6713 which provides real time implementation.

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ANFIS Breast cancer mammograms Artificial Intelligence DSP