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Detection of abnormal brain in MRI via improved AlexNet and ELM optimized by chaotic bat algorithm

  • S. I : Hybridization of Neural Computing with Nature Inspired Algorithms
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Abstract

Computer-aided diagnosis system is becoming a more and more important tool in clinical treatment, which can provide a verification of the doctors’ decisions. In this paper, we proposed a novel abnormal brain detection method for magnetic resonance image. Firstly, a pre-trained AlexNet was modified with batch normalization layers and trained on our brain images. Then, the last several layers were replaced with an extreme learning machine. A searching method was proposed to find the best number of layers to be replaced. Finally, the extreme learning machine was optimized by chaotic bat algorithm to obtain better classification performance. Experiment results based on 5 × hold-out validation revealed that our method achieved state-of-the-art performance.

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Acknowledgement

This paper was partially supported by Royal Society International Exchanges Cost Share Award, UK (RP202G0230); Medical Research Council Confidence in Concept (MRC CIC) Award, UK; Hope Foundation for Cancer Research, UK (RM60G0680); British Heart Foundation Accelerator Award, UK; Guangxi Key Laboratory of Trusted Software (kx201901); and Henan Key Research and Development Project (182102310629); Fundamental Research Funds for the Central Universities (CDLS-2020-03); Key Laboratory of Child Development and Learning Science (Southeast University), Ministry of Education.

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Authors and Affiliations

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

    Siyuan Lu & Yu-Dong Zhang

  2. School of Architecture Building and Civil engineering, Loughborough University, Loughborough, LE11 3TU, UK

    Shui-Hua Wang

  3. School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, 454000, Henan, People’s Republic of China

    Shui-Hua Wang

  4. School of Mathematics and Actuarial Science, University of Leicester, Leicester, LE1 7RH, UK

    Shui-Hua Wang

  5. Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

    Yu-Dong Zhang

  6. Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin, 541004, China

    Yu-Dong Zhang

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  1. Siyuan Lu
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  2. Shui-Hua Wang
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  3. Yu-Dong Zhang
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Correspondence to Shui-Hua Wang or Yu-Dong Zhang.

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Lu, S., Wang, SH. & Zhang, YD. Detection of abnormal brain in MRI via improved AlexNet and ELM optimized by chaotic bat algorithm. Neural Comput & Applic 33, 10799–10811 (2021). https://doi.org/10.1007/s00521-020-05082-4

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