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Classification of Alzheimer’s Disease Based on Eight-Layer Convolutional Neural Network with Leaky Rectified Linear Unit and Max Pooling

  • Image & Signal Processing
  • Published:
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Abstract

Alzheimer’s disease (AD) is a progressive brain disease. The goal of this study is to provide a new computer-vision based technique to detect it in an efficient way. The brain-imaging data of 98 AD patients and 98 healthy controls was collected using data augmentation method. Then, convolutional neural network (CNN) was used, CNN is the most successful tool in deep learning. An 8-layer CNN was created with optimal structure obtained by experiences. Three activation functions (AFs): sigmoid, rectified linear unit (ReLU), and leaky ReLU. The three pooling-functions were also tested: average pooling, max pooling, and stochastic pooling. The numerical experiments demonstrated that leaky ReLU and max pooling gave the greatest result in terms of performance. It achieved a sensitivity of 97.96%, a specificity of 97.35%, and an accuracy of 97.65%, respectively. In addition, the proposed approach was compared with eight state-of-the-art approaches. The method increased the classification accuracy by approximately 5% compared to state-of-the-art methods.

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Acknowledgements

This paper was supported by Open fund of Key Laboratory of Guangxi High Schools Complex System and Computational Intelligence (2016CSCI01), Natural Science Foundation of China (61602250) and Natural Science Foundation of Jiangsu Province (BK20150983), and National Institutes of Health (P50 AG05681, P01 AG03991, R01 AG021910, P50 MH071616, U24 RR021382, R01 MH56584).

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Authors and Affiliations

  1. Department of Informatics, University of Leicester, Leicester, LE1 7RH, UK

    Shui-Hua Wang

  2. Department of Electrical Engineering, The City College of New York, CUNY, New York, NY, 10031, USA

    Shui-Hua Wang

  3. West Virginia School of Osteopathic Medicine, 400 N Lee St, Lewisburg, WV, 24901, USA

    Preetha Phillips

  4. Department of Psychiatry, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing, People’s Republic of China

    Yuxiu Sui

  5. Department of Radiology, Zhong-Da Hospital of Southeast University, Nanjing, 210009, China

    Bin Liu

  6. Department of Radiology, Children’s Hospital of Nanjing Medical University, Nanjing, 210008, People’s Republic of China

    Ming Yang

  7. Department of Neurology, First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China

    Hong Cheng

Authors
  1. Shui-Hua Wang
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  2. Preetha Phillips
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  3. Yuxiu Sui
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  4. Bin Liu
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  5. Ming Yang
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  6. Hong Cheng
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Corresponding authors

Correspondence to Shui-Hua Wang, Preetha Phillips or Hong Cheng.

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We have no conflicts of interest to disclose with regard to the subject matter of this paper.

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This article is part of the Topical Collection on Image & Signal Processing

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Wang, SH., Phillips, P., Sui, Y. et al. Classification of Alzheimer’s Disease Based on Eight-Layer Convolutional Neural Network with Leaky Rectified Linear Unit and Max Pooling. J Med Syst 42, 85 (2018). https://doi.org/10.1007/s10916-018-0932-7

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  • DOI: https://doi.org/10.1007/s10916-018-0932-7

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