BIOLOGICAL EARLY BRAIN CANCER DETECTION USING ARTIFICIAL NEURAL NETWORK
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ABSTRACT:
Identifying Tumors in a MRI images is a useful process. For Tumor identification
classification is done in this paper we use Nero Fuzzy classifier. The MRI images are fist
preprocessed to remove noises from them. Histogram Equalization is done to equalize the contrast
of the image. Then images are enhanced using sharpening filter. Then using gray scale
thresholding the images are segmented. The text in the MRI images is minimized by applying
some Morphological operations. Then GLCM features are extracted from the image. The
extracted features are saved as training features. For query image the same process are done and
the features are stored as test features. True label is set for all the images in the dataset. The test
image features, train image features and True label are passed into the classifier. The Nero Fuzzy
classifier finds if tumor is present or not.
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