Mohamed Maher Ata1, Reem N. Yousef2, Faten Khalid Karim3,*, Doaa Sami Khafaga3
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1597-1616, 2023, DOI:10.32604/csse.2023.034375
Abstract Brain neoplasms are recognized with a biopsy, which is not commonly done before decisive brain surgery. By using Convolutional Neural Networks (CNNs) and textural features, the process of diagnosing brain tumors by radiologists would be a noninvasive procedure. This paper proposes a features fusion model that can distinguish between no tumor and brain tumor types via a novel deep learning structure. The proposed model extracts Gray Level Co-occurrence Matrix (GLCM) textural features from MRI brain tumor images. Moreover, a deep neural network (DNN) model has been proposed to select the most salient features from the GLCM. Moreover, it manipulates the… More >
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