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Quantumedics: Brain Tumor Diagnosis and Analysis Based on Quantum Computing and Convolutional Neural Network

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Proceedings of the 9th International Conference on Advanced Intelligent Systems and Informatics 2023 (AISI 2023)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 184))

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Abstract

Before computer-aided diagnosis tools were created, physicians did physical exams, examined patient histories, and gathered patient data. Medical image analysis used to be laborious and subjective when done manually. Variations and diagnostic errors were also possible. Integrating cutting-edge technology like quantum computing and deep learning into medical image analysis offers great promise. The paper introduces Quantumedics, a system that classifies brain MRI images using a quantum convolutional neural network (QCNN) model and segments tumors using DeepLabV3 +. Data preparation, image classification-based QCNN, and tumor extraction and analysis make up its three primary phases. When a tumor is found, a segmentation model built on DeepLabV3 + is used to precisely define the tumor region. Then, significant information is derived from the tumor region, including the tumor’s laterality and tumor-to-brain ratio. The proposed Quantumedics system is quite promising, according to the experimental findings. In addition, the results showed that DeepLabV3 + outperformed U-Net and earlier versions in terms of segmentation results. Additionally, the outcomes showed that medical experts could utilize the proposed Quantumedics as a diagnosis and analysis tool. Overall, 99% accuracy was attained.

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Authors and Affiliations

  1. School of Computer Science, Canadian International College (CIC), Cairo, Egypt

    Hamza Kamel Ahmed, Baraa Tantawi, Malak Magdy & Gehad Ismail Sayed

Authors
  1. Hamza Kamel Ahmed
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  2. Baraa Tantawi
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  3. Malak Magdy
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  4. Gehad Ismail Sayed
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Corresponding author

Correspondence to Gehad Ismail Sayed .

Editor information

Editors and Affiliations

  1. Faculty of Computers and Information, Cairo University, Giza, Egypt

    AboulElla Hassanien

  2. Port Said University, Port Fouad City, Egypt

    Rawya Y. Rizk

  3. Department of Operations Research and Statistics, The University of Belgrade, Faculty of Organizational Sciences, Belgrade, Serbia

    Dragan Pamucar

  4. Faculty of Science, Helwan University, Cairo, Egypt

    Ashraf Darwish

  5. Shulin District, Fujian University of Technology, New Taipei, Taiwan

    Kuo-Chi Chang

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Ahmed, H.K., Tantawi, B., Magdy, M., Sayed, G.I. (2023). Quantumedics: Brain Tumor Diagnosis and Analysis Based on Quantum Computing and Convolutional Neural Network. In: Hassanien, A., Rizk, R.Y., Pamucar, D., Darwish, A., Chang, KC. (eds) Proceedings of the 9th International Conference on Advanced Intelligent Systems and Informatics 2023. AISI 2023. Lecture Notes on Data Engineering and Communications Technologies, vol 184. Springer, Cham. https://doi.org/10.1007/978-3-031-43247-7_32

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