Multitudinous of remedial medical image using stationary wavelet transform

  • Authors

    • Mrs. S. Meera
    • Mrs. R. Sharmikha Sree
    • Mrs R. Deepika
    • Mrs R. A. Kalpana
    2018-06-08
    https://doi.org/10.14419/ijet.v7i2.33.14840
  • Image Fusion, Stationary Wavelet Transform, Efficient, DWT, Medical Field.
  • Image fusion is becoming more popular in various field nowadays. The quality of accuracy and perception has been achieved with this con-cept. The field that is in urgent need of more contrast images and quality output of body organs image reproduction is medicine. This paper proposes the concept of introducing the image fusion in the area of body imaging to get a more accurate and contrast images for the identifi-cation of the tumor or any other mal-functionalities in the human body. The image fusion is enhanced with the choice of more efficient and contrast uplifting technique called stationary wavelet form. This technique accepts the input of two different perceptive images of the finicky region and enhances their details in the resulting image. The advantageous part of the technique outputs the more detailed edge separation feature which further more allows the fast diagnosis of the any defect prevailing currently in the place subjected to the imaging test. This technique also paves the way to get the more reliable and meticulous result in the future when the world starts embracing the advantage of automation in the field of medicine.

     

  • References

    1. [1] S. Bauer et al., “A survey of MRI-based medical image analysis for brain tumour studies,†Physics in medicine and biology, vol. 58, no. 13, pp. 97–129, 2013.

      [2] D. N. Louis et al., “The 2007 who classification of tumoursof the central nervous system,†Actaneuropathologica, vol. 114, no. 2, pp. 97–109, 2007.

      [3] E. G. Van Meir et al., “Exciting new advances in neurooncology: The avenue to a cure for malignant glioma,†CA: a cancer journal for clinicians, vol. 60, no. 3, pp. 166–193, 2010.

      [4] G. Tabatabai et al., “Molecular diagnostics of gliomas: the clinical perspective,†Acta neuropathologica, vol. 120, no. 5, pp. 585–592, 2010.

      [5] B. Menze et al., “The multimodal brain tumour image segmentation benchmark (brats),†IEEE Transactions on Medical Imaging, vol. 34, no. 10, pp. 1993–2024, 2015.

      [6] N. J. Tustison et al., “N4itk: improved n3 bias correction,†IEEE Transactions on Medical Imaging, vol. 29, no. 6, pp. 1310–1320, 2010.

      [7] L. G. Ny´ul, J. K. Udupa, and X. Zhang, “New variants of a method of MRI scale standardization,†IEEE Transactions on Medical Imaging, vol. 19, no. 2, pp. 143–150, 2000.

  • Downloads

  • How to Cite

    S. Meera, M., R. Sharmikha Sree, M., R. Deepika, M., & R. A. Kalpana, M. (2018). Multitudinous of remedial medical image using stationary wavelet transform. International Journal of Engineering & Technology, 7(2.33), 583-587. https://doi.org/10.14419/ijet.v7i2.33.14840