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Analysis of Segmentation Algorithms for Detection of Anomalies in MR Brain Images

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Advances in Communication Systems and Networks

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 656))

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Abstract

The role of segmentation is vital in image processing for the extraction of region of interest. In the perspective of medical images, the region of interest corresponds to anatomical organs or anomalies such as tumor, cyst. This work analyses various algorithms for the analysis of MR brain images. The clustering-based segmentation technique was found to be efficient and for the validation of results, performance metrics like Jaccard Index, rand index, false positive, and false negative are used. The segmentation algorithms are tested on real-time MR brain and brain web database images. The algorithms are developed in Matlab 2010a and the goal of this research work is to guide the researchers for choosing appropriate algorithm for the analysis of MR brain images.

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Acknowledgements

The authors would like to acknowledge the support provided by Nanyang Technologıcal Unıversıty under NTU Ref: RCA-17/334 for providing the medical images and supporting us in the preparation of the manuscript.

Author information

Authors and Affiliations

  1. Mar Ephraem College of Engineering and Technology, Elavuvilai, India

    A. Lenin Fred & H. Ajay Kumar

  2. Amal Jyothi College of Engineering, Kanjirappally, Kerala, India

    S. N. Kumar

  3. Cognitive Neuroimaging Centre, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore

    Parasuraman Padmanabhan & Balazs Gulyas

Authors
  1. A. Lenin Fred
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  2. S. N. Kumar
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  3. Parasuraman Padmanabhan
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  4. Balazs Gulyas
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  5. H. Ajay Kumar
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Corresponding author

Correspondence to S. N. Kumar .

Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, Mar Baselios College of Engineering and Technology, Thiruvananthapuram, Kerala, India

    J. Jayakumari

  2. Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece

    George K. Karagiannidis

  3. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Maode Ma

  4. Department of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh

    Syed Akhter Hossain

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Lenin Fred, A., Kumar, S.N., Padmanabhan, P., Gulyas, B., Kumar, H.A. (2020). Analysis of Segmentation Algorithms for Detection of Anomalies in MR Brain Images. In: Jayakumari, J., Karagiannidis, G., Ma, M., Hossain, S. (eds) Advances in Communication Systems and Networks . Lecture Notes in Electrical Engineering, vol 656. Springer, Singapore. https://doi.org/10.1007/978-981-15-3992-3_11

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  • DOI: https://doi.org/10.1007/978-981-15-3992-3_11

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  • Publisher Name: Springer, Singapore

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  • Online ISBN: 978-981-15-3992-3

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