An efficient deep learning model for brain tumour detection with privacy preservation

Rehman, Mujeeb Ur; Shafique, Arslan; Khan, Imdad Ullah; Ghadi, Yazeed Yasin; Ahmad, Jawad; Alshehri, Mohammed S.; Al Qathrady, Mimonah; Alhaisoni, Majed; Zayyan, Muhammad H.

Abstract

Internet of medical things (IoMT) is becoming more prevalent in healthcare applications as a result of current AI advancements, helping to improve our quality of life and ensure a sustainable health system. IoMT systems with cutting‐edge scientific capabilities are capable of detecting, transmitting, learning and reasoning. As a result, these systems proved tremendously useful in a range of healthcare applications, including brain tumour detection. A deep learning‐based approach for identifying MRI images of brain tumour patients and normal patients is suggested. The morphological‐based segmentation method is applied in this approach to separate tumour areas in MRI images. Convolutional neural networks, such as LeNET, MobileNetV2, Densenet and ResNet, are tested to be the most efficient ones in terms of detection performance. The suggested approach is applied to a dataset gathered from several hospitals. The effectiveness of the proposed approach is assessed using a variety of metrics, including accuracy, specificity, sensitivity, recall and F‐score. According to the performance evaluation, the accuracy of LeNET, MobileNetV2, Densenet, ResNet and EfficientNet is 98.7%, 93.6%, 92.8%, 91.6% and 91.9%, respectively. When compared to the existing approaches, LeNET has the best performance, with an average of 98.7% accuracy.

Citation

Rehman, M. U., Shafique, A., Khan, I. U., Ghadi, Y. Y., Ahmad, J., Alshehri, M. S., Al Qathrady, M., Alhaisoni, M., & Zayyan, M. H. (online). An efficient deep learning model for brain tumour detection with privacy preservation. CAAI Transactions on Intelligence Technology, https://doi.org/10.1049/cit2.12254

• Journal Article Type: Article
• Acceptance Date: May 23, 2023
• Online Publication Date: Jul 1, 2023
• Deposit Date: Jul 4, 2023
• Publicly Available Date: Jul 4, 2023
• Print ISSN: 2468-2322
• Publisher: Institution of Engineering and Technology (IET)
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1049/cit2.12254
• Keywords: data privacy, medical image processing, deep learning, machine learning