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An Approach to Extract Low-Grade Tumor from Brain MRI Slice Using Soft-Computing Scheme

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Progress in Computing, Analytics and Networking

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1119))

Abstract

The clinical-level assessment of brain Magnetic Resonance Imaging (MRI) varies from the visual/physical examination by a doctor to the Computer-Assisted Evaluation (CAE). Owing to its impact, a number of CAE techniques are planned to assess the brain MRI registered using different modalities. The plan of this research is to build a CAE tool by integrating the thresholding and segmentation techniques, which can effectively work with a range of MRI modalities. This work employs Brain Storm Optimization Algorithm (BSOA) and Otsu’s thresholding and Watershed Segmentation (WS) to extract the tumor section from the considered two-dimensional (2D) MRI slice. The proposed CAE system is tested and validated using the benchmark MRI slices of BRATS2015 database. The examination considered the low-grade tumors of the flair, T1C and T2 modality registered pictures, and its outcome is confirmed with a qualified scrutiny with the Ground Truth (GT) given by an expert. The result of this work substantiates that this CAE tool offered superior values of Image Quality Parameters (IQPs) during the low-grade brain tumor evaluation, and hence, the developed CAE can be considered to inspect the scientific grade MRI slices.

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Author information

Authors and Affiliations

  1. Department of Computer Science Engineering, St. Joseph’s College of Engineering, Chennai, 600 119, Tamilnadu, India

    Sangeetha Francelin Vinnarasi, J. T. Anita Rose &  Jesline

  2. Department of Electronics and Instrumentation, St. Joseph’s College of Engineering, Chennai, 600 119, Tamilnadu, India

    V. Rajinikanth

Authors
  1. Sangeetha Francelin Vinnarasi
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  2. J. T. Anita Rose
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  3. Jesline
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  4. V. Rajinikanth
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Corresponding author

Correspondence to V. Rajinikanth .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India

    Himansu Das

  2. School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India

    Prasant Kumar Pattnaik

  3. School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, India

    Siddharth Swarup Rautaray

  4. Department of Computer Science and Information Engineering (CSIE), Providence University, Taichung, Taiwan

    Kuan-Ching Li

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Vinnarasi, S.F., Rose, J.T.A., Jesline, Rajinikanth, V. (2020). An Approach to Extract Low-Grade Tumor from Brain MRI Slice Using Soft-Computing Scheme. In: Das, H., Pattnaik, P., Rautaray, S., Li, KC. (eds) Progress in Computing, Analytics and Networking. Advances in Intelligent Systems and Computing, vol 1119. Springer, Singapore. https://doi.org/10.1007/978-981-15-2414-1_28

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