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Enhanced Marker-Controlled Watershed Segmentation Algorithm for Brain Tumor Segmentation

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Computational Intelligence in Communications and Business Analytics (CICBA 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1579))

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Abstract

Image processing has always been a vivid area of research that helps mankind unveil the wondrous works. In this paper, the proposed image segmentation algorithm is used to segment the region of interest (ROI) from the MR images. The ultimate idea behind the process of segmentation is to segregate tumor region from the homogenous anatomical structures. The paper proposes an enhanced marker controlled watershed segmentation algorithm which will help in the precise segmentation of the region of interest (ROI) from the provided input image. The Enhanced Marker-Controlled Watershed Segmentation Algorithm helps in identifying the tumor region and segment it such that the tumor can be analyzed for further diagnosis. The proposed method provides a precise accuracy of 99.14% which determines the fact that the tumor region is being segmented accurately with few false positive rate.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, St. Joseph’s College of Engineering, OMR, Chennai, India

    J. Pearline Sheba Grace & P. Ezhilarasi

Authors
  1. J. Pearline Sheba Grace
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  2. P. Ezhilarasi
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Correspondence to J. Pearline Sheba Grace .

Editor information

Editors and Affiliations

  1. Assam University, Silchar, India

    Somnath Mukhopadhyay

  2. Assam University, Silchar, India

    Sunita Sarkar

  3. Visva-Bharati University, Santiniketan, West Bengal, India

    Paramartha Dutta

  4. University of Kalyani, Nadia, India

    Jyotsna Kumar Mandal

  5. Assam University, Silchar, India

    Sudipta Roy

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Grace, J.P.S., Ezhilarasi, P. (2022). Enhanced Marker-Controlled Watershed Segmentation Algorithm for Brain Tumor Segmentation. In: Mukhopadhyay, S., Sarkar, S., Dutta, P., Mandal, J.K., Roy, S. (eds) Computational Intelligence in Communications and Business Analytics. CICBA 2022. Communications in Computer and Information Science, vol 1579. Springer, Cham. https://doi.org/10.1007/978-3-031-10766-5_12

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  • DOI: https://doi.org/10.1007/978-3-031-10766-5_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-10765-8

  • Online ISBN: 978-3-031-10766-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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