Brain Tumor Detection Using Deep Learning (International Journal of Food and Nutritional Sciences, 2022)
On a global basis, brain tumors rank among the leading death factors. Because of itscomplexity and calm nature, this disease is challenging to diagnose in its early stages.Several types of cells give birth to brain tumors, and these cells can provide information onthe type, severity, and rarity of tumors. Tumors can develop in a variety of places, and thelocation of a tumor may reveal information about the sort of cells that are generating it,assisting with further diagnosis. This paper suggests an innovative method to identify andsegment tumor from the MRI images using Deep Learning. We used 3 pre-trained modelsfor training our dataset of brain tumors they are ResNet50, VGG16 model 1 and VGG16model 2. Afterward, we used Convolutional Neural Network (CNN). In our work, among allimplemented models ResNet50 acquired an accuracy of 98.88%, which is really compelling.Its accuracy will help with brain tumor identification and prevention at early stages beforethe tumor results in any physical side effects.