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Neuro-Fuzzy Inference Approach for Detecting Stages of Lung Cancer

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Computational Vision and Bio-Inspired Computing ( ICCVBIC 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1108))

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Abstract

A hybridized diagnosis system called Neuro-Fuzzy Inference System (NFIS) uses neural network for the classification of lung nodule into benign or malignant and then a fuzzy logic for detecting various stages of lung cancer is proposed in this paper. Using fuzzy logic based algorithms such as Enhanced Fuzzy C-Means (EFCM) and Enhanced Fuzzy Possibilistic C-Means (EFPCM), the required features from the lung CT scan image are segmented and extracted using GLCM and GLDM matrix. Then the features are selected using DRASS algorithm. These features are fed as input for Radial Basis Function Neural Network (RBFNN) classifier with k-means learning algorithm for detecting the lung cancer. Once the lung cancerous nodules are detected, the result of RBFNN is combined with fuzzy inference system that determines appropriate stage of the lung cancer. Experiments have been conducted on ILD lung image datasets with 104 cases. Results reveal that our proposed NFIS effectively classify lung nodule into benign or malignant along with the appropriate stage with considerable improvement in respect of Recall/Sensitivity 94.44%, Specificity 92%, Precision 96.22%, Accuracy 93.67%, and False Positive Rate 0.08.

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Acknowledgment

We acknowledge the support extended by VGST, Govt. of Karnataka, in sponsoring this research work vide ref. No. KSTePS/VGST/GRD-684/KFIST(L1)/2018. Dated 27/08/2018.

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Authors and Affiliations

  1. REVA University, Bangalore, 560064, India

    C. Rangaswamy

  2. ECE Department Sambrama Institute of Technology, Bangalore, 560097, India

    C. Rangaswamy

  3. CSE Department RNSIT, Bangalore, 560098, India

    G. T. Raju

  4. ECE School, Reva University, Bangalore, 560064, India

    G. Seshikala

Authors
  1. C. Rangaswamy
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  2. G. T. Raju
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  3. G. Seshikala
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Corresponding author

Correspondence to C. Rangaswamy .

Editor information

Editors and Affiliations

  1. Department of CSE, RVS Technical Campus, Coimbatore, India

    S. Smys

  2. Faculty of Engineering, Faculdade de Engenharia da Universidade do Porto, Porto, Portugal

    João Manuel R. S. Tavares

  3. Faculty of Engineering, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  4. School of Computing, Tokyo Institute of Technology, Tokyo, Japan

    Abdullah M. Iliyasu

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✓ All authors declare that there is no conflict of interest

✓ No humans/animals involved in this research work.

✓ We have used our own data.

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Rangaswamy, C., Raju, G.T., Seshikala, G. (2020). Neuro-Fuzzy Inference Approach for Detecting Stages of Lung Cancer. In: Smys, S., Tavares, J., Balas, V., Iliyasu, A. (eds) Computational Vision and Bio-Inspired Computing. ICCVBIC 2019. Advances in Intelligent Systems and Computing, vol 1108. Springer, Cham. https://doi.org/10.1007/978-3-030-37218-7_51

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