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Detection of Cancer Cell Growth in Lung Image Using Artificial Neural Network

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

Author

Listed:
  • R. Pandian

    (Sathyabama Institute of Science and Technology, School of EEE)

  • S. LalithaKumari

    (Sathyabama Institute of Science and Technology, School of EEE)

  • R. Raja Kumar

    (Sathyabama Institute of Science and Technology, School of EEE)

Abstract

Image compression finds an exhaustive application in the field of medical image file storage. Image files contain considerable amount of redundant and irrelevant data and suitable image compression algorithms can be used to eliminate this. In this paper, Coiflet wavelet is used to perform the compression for computer tomography image of coronel view. The CT images are encoded using the different types of encoding techniques .The performances of compression are measured in terms of PSNR, Compression ratio, Means square error and bits per pixel. The Image texture features are extracted, and it is proven that after compression and further it can be used for classification of images.

Suggested Citation

  • R. Pandian & S. LalithaKumari & R. Raja Kumar, 2020. "Detection of Cancer Cell Growth in Lung Image Using Artificial Neural Network," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 1465-1469, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-41862-5_150
    DOI: 10.1007/978-3-030-41862-5_150
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