Classification of Heart Disease from MRI Images Using Convolutional Neural Network

In this paper, we have demonstrated a CAD architecture for heart disease based on the Convolutional Neural Network. Heart disease is one of the major problems in worldwide and killing millions of people. The computational method with the help of Deep learning has the potential to early detection the disease to save lives. Data we have collected in the form of MRI images from the online resources. After preprocessing and normalization we have trained our model with the help of the convolution neural network (CNN). The image data set is divided into the training set and validation sets obtain an accuracy of 95% which is good as compare to the other methods. The model is compared with the state-of-the-art available model like Linear, 3D Google net, Vanilla 3D CNN. The model performed better are compare to the existing models.