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

  • Sangeetha Francelin Vinnarasi
  • J. T. Anita Rose
  • Jesline
  • V. RajinikanthEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1119)


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.


Brain MRI Otsu Brain storm optimization algorithm Watershed segmentation Validation 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Sangeetha Francelin Vinnarasi
    • 1
  • J. T. Anita Rose
    • 1
  • Jesline
    • 1
  • V. Rajinikanth
    • 2
    Email author
  1. 1.Department of Computer Science EngineeringSt. Joseph’s College of EngineeringChennaiIndia
  2. 2.Department of Electronics and InstrumentationSt. Joseph’s College of EngineeringChennaiIndia

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