Brain Tumour Classification using Artificial Neural Networks: A Survey
DOI:
https://doi.org/10.26438/ijcse/v6i5.686690Keywords:
Artificial Intelligence (AI), Artificial Neural Network (ANN), Discrete Wavelet Transform (DWT), Principal Component Analysis (PCA), adaptive thresholding, binarizationAbstract
Artificial Intelligence (AI) is making its presence felt in diverse areas. One such area which has been invaded by artificial intelligence is brain tumour classification using Artificial Neural Networks because of the complexity in human intervention based approaches. Automated classification reduces the possibility of human errors and reinforces classification at hindsight. The entire process of classification using Artificial Neural Networks (ANN) can be broadly bifurcated into two steps viz. Feature Extraction and Classification. Here, in the proposed paper, a survey on the various mathematical tools required for the feature extraction and classification of brain tumour cases using MRI images is put forth and analyzed. Also previous work and their salient features have been cited.
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