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An Integrated Design of Fuzzy C-Means and NCA-Based Multi-properties Feature Reduction for Brain Tumor Recognition

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Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems

Abstract

In medical imaging, brain tumor detection and recognition from magnetic resonance imaging examination are essential for both the analysis and processing of brain cancers. From the literature, it is quite clear that the recognition of brain tumors with high accuracy depends on the multi-levels features fusion. In this book chapter, we proposed an integrated framework for brain tumor recognition based on fuzzy C-means and multi-properties feature reduction. Three primary steps are involved in this work. In the first step, auto-skull stripping and tumor contrast stretching is performed through a combination of well-known filtering methods, and then segment the tumor region by fuzzy C-means. In the second step, multi-properties features are fused such as shape, texture, point, and Gabor wavelet by weights assignment. In the third step, NCA (neighborhood component analysis)-based irrelevant features are removed from fused feature vector (FV). The final compressed FV is fed to one-against-all support vector machine and achieved an accuracy of 100% and 96.3% on BRATS2013 and BRATS2015 dataset, respectively. Comparison with other techniques shows that the NCA-based reduction approach outperforms on selected datasets.

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Author information

Authors and Affiliations

  1. Department of Computer Science, HITEC University, Taxila, Pakistan

    Muhammad Attique Khan & Muhammad Younus Javed

  2. Department of CS, COMSATS University Islamabad, Islamabad, Pakistan

    Habiba Arshad, Wasif Nisar & Muhammad Sharif

Authors
  1. Muhammad Attique Khan
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  2. Habiba Arshad
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  3. Wasif Nisar
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  4. Muhammad Younus Javed
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  5. Muhammad Sharif
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Editor information

Editors and Affiliations

  1. Electronics and Communication Engineering, Sri Sairam Engineering College, Chennai, Tamil Nadu, India

    E. Priya

  2. Electronics and Instrumentation Engineering, St. Joseph’s College of Engineering, Chennai, Tamil Nadu, India

    V. Rajinikanth

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Khan, M.A., Arshad, H., Nisar, W., Javed, M.Y., Sharif, M. (2021). An Integrated Design of Fuzzy C-Means and NCA-Based Multi-properties Feature Reduction for Brain Tumor Recognition. In: Priya, E., Rajinikanth, V. (eds) Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-6141-2_1

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