Feature Extraction of Brain Tumour Images for Classification Benign and Malignant Type Tumours using PCA, DWT, and ANN

Abstract

One of the most important areas which have been invaded by artificial intelligence is feature extraction and classification of biomedical data. One such area which has been invaded by artificial intelligence is brain tumor classification using Artificial Neural Networks. In this paper, we present a technique that computes the features of images containing brain tumors. Features have been computed after pre-processing the images containing brain tumors. Pre-processing has been achieved using gray scaling and thresholding. Discrete wavelet transform dwt has been utilized as an instrument to evacuate the unexpected varieties in the determined element esteems head segment investigation PCA has been utilized to discover specific patterns in the registered element information and limit the redundancy The feature extraction stage paves the path for further classification of the data using Neural Networks.