Deriving tumor detection models using convolutional neural networks from MRI of human brain scans

Abstract

Convolutional Neural Networks (CNNs) is a deep learning model used for image classification. The objective of our work is to analyze the different CNN models in the classification of benign tumor slices from MRI brain volumes and select a suitable CNN model for brain tumor detection. In this paper, we have developed six CNN models and trained using BraTS2013 dataset and tested with the WBA dataset. We have inferred the results for all the six models. The best model for classification of tumor slices is found among the six models. The accuracy of each and every model is recorded. Our models have attained about 96–99% of accuracy.