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Advanced Computing and Intelligent Technologies pp 211–223Cite as

Efficient Diagnosis of Alzheimer’s Disease Using EfficientNet in Neuroimaging

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Part of the Lecture Notes in Electrical Engineering book series (LNEE,volume 914)

Abstract

Alzheimer's disease is a progressive disease that weakens mind’s memory and overall functioning. In the early identification of Alzheimer's disease, neuroimaging is increasingly being utilized to support clinical examinations (AD). One of the most commonly utilized and promising modalities for detecting brain abnormalities in persons who may be at risk for AD but have not yet exhibited symptoms is structural magnetic resonance imaging (MRI). In this study, a transfer learning model called EfficietNetB7 architecture is analyzed to enhance the prediction with pre-trained weights in a benchmark dataset of neuroimages. The network is further fine-tuned via layer-wise tuning, which involves training a pre-defined set of layers using MRI images. The performance of the proposed system is evaluated over the Kaggle brain MRI dataset that includes four classes such as mild demented, moderately demented, non-demented, and very mildly demented. For AD classification, the proposed trained model achieves enhanced accuracy and F1-score as 89.7% and 0.91, respectively.

Keywords

  • Deep learning
  • Transfer learning
  • MRI
  • Neuroimaging
  • Artificial intelligence
  • Alzheimer's disease
  • EfficientNet

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  • DOI: 10.1007/978-981-19-2980-9_18
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Authors and Affiliations

  1. School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India

    H. Sharen, B. Dhanush & P. Rukmani

  2. Mar Ephraem College of Engineering and Technology, Marthandam, India

    D. Dhanya

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  1. H. Sharen
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  2. B. Dhanush
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  3. P. Rukmani
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  4. D. Dhanya
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Corresponding author

Correspondence to H. Sharen .

Editor information

Editors and Affiliations

  1. Bharath Institute of Higher Education and Research, Chennai, Tamil Nadu, India

    Rabindra Nath Shaw

  2. Regional Campus Manipur, Indira Gandhi National Tribal University, Imphal, Manipur, India

    Sanjoy Das

  3. Department of Computer Science, University of Milan, Milan, Italy

    Vincenzo Piuri

  4. Department of Information Engineering and Mathematics, University of Siena, Siena, Italy

    Monica Bianchini

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Sharen, H., Dhanush, B., Rukmani, P., Dhanya, D. (2022). Efficient Diagnosis of Alzheimer’s Disease Using EfficientNet in Neuroimaging. In: Shaw, R.N., Das, S., Piuri, V., Bianchini, M. (eds) Advanced Computing and Intelligent Technologies. Lecture Notes in Electrical Engineering, vol 914. Springer, Singapore. https://doi.org/10.1007/978-981-19-2980-9_18

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  • DOI: https://doi.org/10.1007/978-981-19-2980-9_18

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