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A Modified Undecimated Discrete Wavelet Transform Based Approach to Mammographic Image Denoising

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Abstract

In this work, the authors present an effective denoising method to attempt reducing the noise in mammographic images. The method is based on using hierarchical correlation of the coefficients of discrete stationary wavelet transforms. The features of the proposed technique include iterative use of undecimated multi-directional wavelet transforms at adjacent scales. To validate the proposed method, computer simulations were conducted, followed by its applications to clinical mammograms. Mutual information originating from information theory was used as an evaluation measure for selection of an optimal wavelet basis function. We examined the performance of the proposed method by comparing it with the conventional undecimated discrete wavelet transform (UDWT) method in terms of processing time-consuming and image quality. Our results showed that with the use of the proposed method the computation time can be reduced to approximately 1/10 of the conventional UDWT method consumed. The results of visual assessment indicated that the images processed with the proposed UDWT method showed statistically significant superior image quality over those processed with the conventional UDWT method. Our research results demonstrate the superiority and effectiveness of the proposed approach.

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Acknowledgments

This research was supported in part by a Grant-in-Aid for Scientific Research (23602004) from the Japan Society for the Promotion of Sciences (JSPS). The authors also would like to thank the observers for their participation in visual evaluation.

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Authors and Affiliations

  1. Department of Radiological Technology, Graduate School of Health Sciences, Niigata University, 2-746, Asahimachi-dori, Niigata, 951-8518, Japan

    Eri Matsuyama, Du-Yih Tsai, Yongbum Lee & Haruyuki Watanabe

  2. Department of Radiology, Nakajo Central Hospital, Niigata, Japan

    Masaki Tsurumaki

  3. Department of Radiology, Sendai City Hospital, Sendai, Japan

    Noriyuki Takahashi

  4. Department of Biomedical Engineering, Hungkuang University, Taichung, Taiwan

    Hsian-Min Chen

Authors
  1. Eri Matsuyama
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  2. Du-Yih Tsai
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  4. Masaki Tsurumaki
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  5. Noriyuki Takahashi
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  7. Hsian-Min Chen
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Correspondence to Du-Yih Tsai.

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Matsuyama, E., Tsai, DY., Lee, Y. et al. A Modified Undecimated Discrete Wavelet Transform Based Approach to Mammographic Image Denoising. J Digit Imaging 26, 748–758 (2013). https://doi.org/10.1007/s10278-012-9555-6

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