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    ARTICLE

    Leveraging EfficientNetB3 in a Deep Learning Framework for High-Accuracy MRI Tumor Classification

    Mahesh Thyluru Ramakrishna1, Kuppusamy Pothanaicker2, Padma Selvaraj3, Surbhi Bhatia Khan4,7,*, Vinoth Kumar Venkatesan5, Saeed Alzahrani6, Mohammad Alojail6

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 867-883, 2024, DOI:10.32604/cmc.2024.053563 - 15 October 2024

    Abstract Brain tumor is a global issue due to which several people suffer, and its early diagnosis can help in the treatment in a more efficient manner. Identifying different types of brain tumors, including gliomas, meningiomas, pituitary tumors, as well as confirming the absence of tumors, poses a significant challenge using MRI images. Current approaches predominantly rely on traditional machine learning and basic deep learning methods for image classification. These methods often rely on manual feature extraction and basic convolutional neural networks (CNNs). The limitations include inadequate accuracy, poor generalization of new data, and limited ability… More >

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