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Enhancing the Quality of Medical Image Database Based on Kernels in Bandelet Domain

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Future Data and Security Engineering (FDSE 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9446))

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Abstract

Diagnostic imaging has contributed significantly to improving the accuracy, timeliness and efficiency of healthcare. Most of medical images have blur combined with noise because of many reasons. This problem will give difficulties to health professionals because each of small details is very useful for the treatment process of doctors. In this paper, we proposed a new method to improve the quality of medical images. The proposed method includes two steps: denoising by Bayesian thresholding in bandelet domain and using the Kernels set for deblurring. We undervested the proposed method by calculating the PSNR and MSE values. This method gives the result better than the other recent methods available in literature.

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Author information

Authors and Affiliations

  1. Faculty of Computer Science and Engineering, Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam

    Nguyen Thanh Binh

Authors
  1. Nguyen Thanh Binh
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Corresponding author

Correspondence to Nguyen Thanh Binh .

Editor information

Editors and Affiliations

  1. Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam

    Tran Khanh Dang

  2. Johannes Kepler University Linz, Linz, Austria

    Roland Wagner

  3. Johannes Kepler University Linz, Linz, Austria

    Josef Küng

  4. Ho Chi Minh City University of Technology, Ho Chi Minh City, Vietnam

    Nam Thoai

  5. Hosei University, Tokyo, Japan

    Makoto Takizawa

  6. University of Vienna, Vienna, Austria

    Erich Neuhold

Appendix

Appendix

See Tables A1, A2, A3, A4.

Table A1. PSNR values (dB) of different denoised and deblured images with Gaussian blur combined with Gaussian noise.
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Table A2. PSNR values (dB) of different denoised and deblured images with motion blur combined with Gaussian noise.
Full size table
Table A3. MSE values of different denoised and deblured images with Gaussian blur combined with Gaussian noise.
Full size table
Table A4. MSE values of different denoised and deblured images with motion blur combined with Gaussian noise.
Full size table

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Binh, N.T. (2015). Enhancing the Quality of Medical Image Database Based on Kernels in Bandelet Domain. In: Dang, T., Wagner, R., Küng, J., Thoai, N., Takizawa, M., Neuhold, E. (eds) Future Data and Security Engineering. FDSE 2015. Lecture Notes in Computer Science(), vol 9446. Springer, Cham. https://doi.org/10.1007/978-3-319-26135-5_17

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  • DOI: https://doi.org/10.1007/978-3-319-26135-5_17

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