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Application of KPCA and AdaBoost algorithm in classification of functional magnetic resonance imaging of Alzheimer’s disease

  • S.I. : ATCI 2019
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Neural Computing and Applications Aims and scope Submit manuscript

Abstract

With the rapid development of modern brain imaging techniques and big data analysis that measures brain processes, researchers are increasingly looking to reveal the pathogenesis of Alzheimer’s disease. In order to find effective classification of magnetic resonance images of Alzheimer’s disease, this paper constructed a feature classification model for Alzheimer’s disease based on AdaBoost algorithm and KPCA algorithm, and selected 21 patients with Alzheimer’s disease (AD). The trial included 6 patients with advanced Alzheimer’s disease (LAD), 7 patients with early Alzheimer’s disease, and 8 healthy individuals (HC) who underwent different levels of analysis. The results show that the article uses the KPCA algorithm to obtain the highest classification accuracy of the two groups: 94.77%, the single feature distinguishing ability is the node degree, and the accuracy of 90.94% can be achieved in the imaging diagnosis of AD. The article can significantly improve the classification of magnetic resonance images of Alzheimer’s disease. This result is a good test of the effectiveness of the selected algorithm and has profound clinical significance for the diagnosis and classification of AD using magnetic resonance imaging.

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Acknowledgements

This work was supported by: (1) Studying Abroad Scholarships by Department of Resource and Social Security of Shanxi Province (Grant/Award: 619017); (2) Shanxi scholarship council of China (Grant/Award No. 2016-061); (3) International Cooperation Project, the Shanxi Science and Technology Department (Grant/Award No. 201803D421068).

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Authors and Affiliations

  1. Institute of Geriatrics, Shanxi Medical University, Taiyuan, 030001, China

    Zhao Fan

  2. School of Stomatology, Shanxi Medical University, Taiyuan, 030001, China

    Fanyu Xu

  3. Department of Physiology, Basic Medical of Sciences, Shanxi Medical University, Taiyuan, 030001, China

    Cai Li & Lili Yao

Authors
  1. Zhao Fan
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  2. Fanyu Xu
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  3. Cai Li
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  4. Lili Yao
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Correspondence to Zhao Fan.

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Fan, Z., Xu, F., Li, C. et al. Application of KPCA and AdaBoost algorithm in classification of functional magnetic resonance imaging of Alzheimer’s disease. Neural Comput & Applic 32, 5329–5338 (2020). https://doi.org/10.1007/s00521-020-04707-y

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  • DOI: https://doi.org/10.1007/s00521-020-04707-y

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