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Multi-view convolutional neural network with leader and long-tail particle swarm optimizer for enhancing heart disease and breast cancer detection

  • S.I. : 2018 India Intl. Congress on Computational Intelligence
  • Published:
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Abstract

As the core of deep learning methodologies, convolutional neural network (CNN) has received wide attention in the area of image recognition. In particular, it requires very precise, accurate and fine recognition power for medical imaging processing. Numerous promising prospects of CNN applications with medical prognosis and diagnosis have been reported in the related works, and the common goal among the literature is mainly to analyze the insights from the finest details of medical images and build a more suitable model with maximum accuracy and minimum error. Thus, a novel CNN model is proposed with the characteristics of multi-view feature preprocessing and swarm-based parameter optimization. Additional information of extra features from multi-view is discovered potentially for training, and simultaneously, the most optimal set of CNN parameters are provided by our proposed leader and long-tail-based particle swarm optimization. The purpose of such a hybrid method is to achieve the highest possibility of target recognition in medical images. Preliminary experiments over cardiovascular and mammogram datasets related to heart disease prediction and breast cancer classification, respectively, are designed and conducted, and the results indicate encouraging performance compared to other existing CNN model optimization methods.

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Acknowledgements

The authors are thankful to the financial support from the research grants, MYRG2016-00069, offered by the Multi-Year Research Grant (MYRG) of University of Macau, and FDCT/126/2014/A3, offered by the Science and Technology Development Fund (FDCT) of Macau SAR government.

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Author notes

  1. Kun Lan and Liansheng Liu have contributed equally to this work.

Authors and Affiliations

  1. Department of Management Science and Information System, Faculty of Management and Economics, Kunming University of Science and Technology, Kunming, Yunnan, China

    Rui Tang

  2. Department of Medical Imaging, First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China

    Liansheng Liu

  3. Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macau SAR, China

    Kun Lan, Tengyue Li, Yuhao Chen & Simon Fong

  4. School of Business, University of Saint Joseph, Macau SAR, China

    Joao Alexandre Lobo Marques

  5. School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, Australia

    Raymond K. Wong

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  1. Kun Lan
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Correspondence to Rui Tang.

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Lan, K., Liu, L., Li, T. et al. Multi-view convolutional neural network with leader and long-tail particle swarm optimizer for enhancing heart disease and breast cancer detection. Neural Comput & Applic 32, 15469–15488 (2020). https://doi.org/10.1007/s00521-020-04769-y

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