Anfis to Detect Brain Tumor Using MRI


  • Susmita Mishra
  • M Prakash
  • A Hafsa
  • G Anchana





Brain tumour, magnetic reasonance imaging(MRI), image preprocessing, adaptive histogram equalisation(AHE), adaptive neural network(ANN), fuzzy logic.


Processing of Magnetic Resonance Imaging(MRI) is one of the widely known best techniques to diagnose brain tumor since it gives better results than ultrasound or X-Ray images. The main objective is to diagnose the presence and extraction of brain tumor using MRI images. Image preprocessing includes contrast stretching, noise filtering and Adaptive Histogram Equalization(AHE). AHE gives a graphical representation of digital image without enhancing above the desired level. The next stage involves transferring the redundant information in input image to reduced set of features is called feature selection and is done by color, shape or texture of an image. Image is segmented using incorporation of Artificial Neural Networks(ANN) and Fuzzy logic called Adaptive Neuro-Fuzzy Inference System(ANFIS) wherein we get the desired output to differentiate tumor affected and normal image with its severity level. Since we deal with uncertainty much more, fuzzy logic serves as a vibrant tool in representing human knowledge as IF-THEN rules. MATLAB has been implemented in detection and extraction of tumor at an early stage.



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