Abstract
AbstractRecently, deep learning techniques have achieved significant success in medical image analysis. In this article, deep learning methods have been applied to separate brain magnetic resonance (MR) images into different abnormalities and healthy classes. The sectional brain MR of brain images is used as a database from the Open Access Imaging Studies Series (OASIS). Based on Convolutional Neural Network (CNN) method for classification and a thresholding algorithm for image segmentation, the system has been developed. The images that are improved by image processing are transferred to the CNN deep learning model and the classification process is done. Adam algorithm was used as the optimization algorithm for the classification process. As a result of the classification, 80% accuracy rate was obtained. The model’s loss rate fell to 0.3 s.KeywordsDeep learningConvolution Neural NetworkMRMedical imagingOASIS
Published Version
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