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A Novel Region Based Thresholding for Dental Cyst Extraction in Digital Dental X-Ray Images

In: New Trends in Computational Vision and Bio-inspired Computing

Author

Listed:
  • R. Karthika Devi

    (Sethu Institute of Technology)

  • A. Banumathi

    (Thiagarajar College of Engineering)

  • G. Sangavi

    (Sethu Institute of Technology)

  • M. Sheik Dawood

    (Sethu Institute of Technology)

Abstract

The proposed Maximally Stable Extremal Regions (MSER) algorithm extracts stable connected component of an available set of gray levels in an image. The maximal intensity regions may appear, grow, and merge at different intensity value of thresholds. The Stability achieved through a finding of extremal regions whose support of region is virtually unchanged over a range of thresholds selection. Therefore the regional intensity variation of cyst makes the MSER algorithm perfect, to do cyst boundary extraction in digital dental x-ray images. The results of the MSER based cyst segmentation in dental x-ray images show that there is a significant correlation found between the cystic region extracted by the medical experts .The cystic area segmented by the proposed MSER method results in extraction of the dental cystic boundary very efficiently and accurately.

Suggested Citation

  • R. Karthika Devi & A. Banumathi & G. Sangavi & M. Sheik Dawood, 2020. "A Novel Region Based Thresholding for Dental Cyst Extraction in Digital Dental X-Ray Images," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 1633-1640, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-41862-5_167
    DOI: 10.1007/978-3-030-41862-5_167
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