DeepGAN: An Enhanced Approach for Detecting Brain Tumor

Abstract

Brain Tumor is a major disease that affected in children and adults. This happens when changes occur in brain cell development and may lead the cells to partition uncontrolled and turbulently. Misclassification of these tumor cells may lead to consequences. The main objective of our examination is to distinguish the powerful and prescient calculation for the identification of bosom malignant growth, utilizing AI calculations, and figure out the best way concerning exactness and accuracy. DeepGAN is a neural network model proposed for identifying and detecting brain Tumors in the MRI images of patients. The raw MRI images are preprocessed and then passed to the generator and discriminator of the proposed model in order to extract salient features and detect a tumor. The proposed model is evaluated on computing precision, recall, specificity, sensitivity, and accuracy. From the experimental results, the DeepGAN model outperforms with 99% of accuracy on detecting tumors.