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A Multi-Class Brain Tumor Classifier using Convolutional Neural Network with 99% Accuracy achieved by applying the method of Transfer Learning using Python and Pytorch Deep Learning Framework
We segmented the Brain tumor using Brats dataset and as we know it is in 3D format we used the slicing method in which we slice the images in 2D form according to its 3 axis and then giving the model for training then combining waits to segment brain tumor. We used UNET model for our segmentation.
A Brain Tumor Classification and Segmentation tool to easily detect from Magnetic Resonance Images or MRI. It works on a Convolutional Neural Network created using Keras.
Brain Tumor Radiogenomic Classification task solved by Transfer Learning at Universitat de Barcelona and Universitat Politècnica de Catalunya · BarcelonaTech