Brain tumor magnetic resonance image classification: a deep learning approach

From the past decade, many researchers are focused on brain tumor detection mechanism using magnetic resonance images. The traditional approaches follow feature extraction process from bottom layer in network. This scenario is not suitable to medical To address this issue, proposed model employed Inception-v3 convolution neural network which a deep learning mechanism. extracts multi-level features and classifies them find early of tumor. uses approach hyper parameters. These parameters optimized Adam Optimizer loss function. function helps machines algorithm with input data. softmax classifier used classify images multiple classes. It observed that accuracy recorded as 99.34% training data 89% at validation