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A Survey of Multi-Abnormalities Disease Detection and Classification in WCE

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

Author

Listed:
  • R. Ponnusamy

    (Annamalai University, Department of Computer and Information Science)

  • S. Sathiamoorthy

    (Annamalai University, Department of Computer and Information Science)

  • R. Visalakshi

    (Annamalai University, Department of Information Technology)

Abstract

This paper reviews on detection and classification of multi-abnormalities occur in small bowel region. Multi-abnormalities like ulcer, bleeding, polyp and tumor are caught by utilizing Wireless Capsule Endoscopy (WCE). WCE images are utilized to diagnosis the infections in the stomach related tract. To identify and detect the diseases which occur in small bowl is difficult for human to recognize the exact type of disease. To overcome this problem, various Image processing and machine learning techniques are utilized over the decade to detect and identify the diseases more accurately are discussed in this paper.

Suggested Citation

  • R. Ponnusamy & S. Sathiamoorthy & R. Visalakshi, 2020. "A Survey of Multi-Abnormalities Disease Detection and Classification in WCE," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 889-898, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-41862-5_90
    DOI: 10.1007/978-3-030-41862-5_90
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