MRI image classification using GLCM texture features

The uncovering Brain Tumour is a challenging problem due to the structure of the Tumour cells. The proposed work presents a sorting method for classifying Magnetic Resonance images to detect the Brain Tumour in its early stages and to analyze anatomical structures. The probabilistic neural network with radial basis function (PNN-RBF) will be engaged to implement an automated Brain Tumour classification and To regulate the stages of Brain Tumour that is benign, malignant or normal. Decision shaping was performed in two stages: feature extraction using FDCT, gray level co-occurrence matrix (GLCM) and the classification using PNN-RBF network. The depiction of this classifier was evaluated in terms of training performance and classification accuracies. The simulated results will be show that PNN classifier provides better accuracy than the existing methods.

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