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A Fusion-Based Convolutional Fuzzy Neural Network for Lung Cancer Classification

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Abstract

Among cancer types, lung cancer has one of the highest mortality rates worldwide. Clinicians currently use magnetic resonance imaging or computed tomography (CT) to diagnose lung cancer in patients. For lung cancer detection, improving the accuracy of diagnosis or detection through CT is a challenging task. Therefore, this study proposes a fusion-based convolutional fuzzy neural network (F-CFNN) that identifies and classifies CT images. The F-CFNN has a convolutional fuzzy neural network (CFNN) that uses two convolutional and two pooling layers to extract features and utilizes a fuzzy neural network to provide robust classification results. Furthermore, five fusion methods are used, namely global max pooling (GMP), global average pooling (GAP), channel global max pooling (CGMP), channel global average pooling (CGAP), and network mapping fusion (NMF). In the F-CFNN, parameter selection is generally conducted through trial-and-error; therefore, the Taguchi method is applied to identify the optimal parameter combination of the network. To validate the proposed method, the SPIE-AAPM public data set is used in this experiment. The experimental results indicate that the classification accuracy of the F-CFNN with NMF is 93.26%. In addition, after the Taguchi method is applied to identify the optimal parameter combination, the classification accuracy of the Taguchi-based F-CFNN with NMF is increased to 99.98%.

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Acknowledgements

The authors would like to thank the Ministry of Science and Technology of the Republic of China, Taiwan, for financially supporting this research under Contract No. MOST 108-2221-E-167-026.

Funding

This research was funded by the Ministry of Science and Technology of the Republic of China, Grant Number MOST 110-2221-E-167-031-MY2.

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Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Chin-Yi University of Technology, Taichung, 411, Taiwan

    Cheng-Jian Lin & Tang-Yun Yang

  2. College of Intelligence, National Taichung University of Science and Technology, Taichung, 404, Taiwan

    Cheng-Jian Lin

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  1. Cheng-Jian Lin
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  2. Tang-Yun Yang
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Correspondence to Cheng-Jian Lin.

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Lin, CJ., Yang, TY. A Fusion-Based Convolutional Fuzzy Neural Network for Lung Cancer Classification. Int. J. Fuzzy Syst. 25, 451–467 (2023). https://doi.org/10.1007/s40815-022-01399-5

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  • DOI: https://doi.org/10.1007/s40815-022-01399-5

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