Classification of celebral Gliomas (HGG,LGG) based on MRI using deep learning

.In these work i do a classification of cerebral gliomas using deep learnig which several Convolutional Neural Network models were used

including ResNet50, VGG16 and Xception which were trained on the BraTS2018

dataset added to BraTS2019 in order to overcome the challenge of data scarcity. The

modeling architecture consists of the base models (ResNet50, VGG16, Xception)

with additional layers such as Dense Layers, Batch Normalization and Dropout that

was used to avoid overfitting. The Adam optimizer was used to train the models

while Sparse Categorical Crossentropy Loss and Accuracy metrics were used to

evaluate them.

i add also a user django interface to facilate the load of MRI image of the patient from button load and see the result of classification (HGG,LGG) with the percentage of each like in photos .