Skip to main content

Method for reducing noise in X-ray images by averaging pixels based on the normalized difference with the relevant pixel

Radiological Physics and Technology volume 1, pages 188–195 (2008)Cite this article

Abstract

A real-time digital filter for noise reduction in X-ray images is proposed. The filter is based on averaging of only similar pixels (pixels that differ only little) rather than neighboring pixels, which are averaged in conventional linear low-pass filters. The effectiveness of the filter was evaluated by computer simulation, where original images that were acquired by X-ray exposure were processed in accordance with the filter algorithm. The resulting images were evaluated in terms of the pre-sampled modulation transfer function (MTF), the noise power spectrum (NPS), and the lag. Comparison of the filtered and original images revealed that the NPS was reduced for the full range of spatial frequencies in the filtered image, resulting in a reduction of total noise power to about 1/9 the level in the original image with no degradation in the MTF or lag. The usefulness of the filter was demonstrated in fluoroscopic, digital subtraction angiography (DSA) and mammographic phantom studies. The filter was found to have the potential to reduce the patient dose by reducing the noise in dynamic as well as static X-ray images.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

43,34 €

Price includes VAT (Finland)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

References

  1. Maolinbay M, El-Mohri Y, Antonuk LE, Jee K-W, Nassif S, Rong X, et al. Additive noise properties of active matrix flat-panel imagers. Med Phys. 2000;27:1841–54.

    CAS  Article  PubMed  Google Scholar 

  2. El-Mohri Y, Antonuk LE, Zhao Q, Maolinbay M, Rong X, Jee K-W, et al. A quantitative investigation of additive noise reduction for active matrix flat-panel imagers using compensation lines. Med Phys. 2000;27:1855–64.

    CAS  Article  PubMed  Google Scholar 

  3. Zhao W, Rowlands JA. X-ray imaging using amorphous selenium: feasibility of a flat panel self-scanned detector for digital radiology. Med Phys. 1995;22:1595–604.

    CAS  Article  PubMed  Google Scholar 

  4. Barrett HH, Swindell W. Radiological imaging. New York: Academic; 1981. p. 29–61.

  5. Jaffe CC, Orphanoudakis SC, Ablow RC. The effect of a television digital noise reduction device on fluoroscopic image quality and dose rate. Radiology. 1982;144:789–92.

    CAS  Article  PubMed  Google Scholar 

  6. Funama Y, Awai K, Miyazaki O, Nakayama Y, Goto T, Omi Y, et al. Improvement of low-contrast detectability in low-dose hepatic multidetector computed tomography using a novel adaptive filter: evaluation with a computer-simulated liver including tumors. Invest Radiol. 2006;41:1–7.

    Article  PubMed  Google Scholar 

  7. Sasaki T, Hanari T, Sasaki M, Oikawa H, Gakumazawa H, Okumura M, et al. Reduction of radiation exposure in CT perfusion study using a quantum de-noising filter. Jpn J Radiol Technol. 2004;60:1688–93 [in Japanese].

    Google Scholar 

  8. Honda M, Shiraishi K. An image processing method for fluoroscopy using a linear shadow detection. Med Imaging and Inf Sci. 2004;21:239–51 [in Japanese].

    Google Scholar 

  9. Saito N, Kudo K, Sasaki T, Uesugi M, Koshino K, Miyamoto M, et al. Realization of reliable cerebral-blood-flow maps from low-dose CT perfusion images by statistical noise reduction using nonlinear diffusion filtering. Radiol Phys Technol. 2008;1:62–74.

    Article  PubMed  Google Scholar 

  10. Vuylsteke P, Dewaele P. Method and apparatus for noise reduction. US Patent 5,461,655;1995.

  11. Yamada S, Murase K. Effectiveness of flexible noise control image processing for digital portal images using computed radiography. Br J Radiol. 2005;78:519–27.

    CAS  Article  PubMed  Google Scholar 

  12. Nambu K, Iseki H. A noise reduction method based on a statistical test of high dimensional pixel vectors for dynamic and volumetric images. Riv Neuroradiol. 2005;18:21–33.

    Article  Google Scholar 

  13. Samei E, Flynn MJ, Reimann DA. A method for measuring the presampled MTF of digital radiographic systems using an edge test device. Med Phys. 1998;25:102–13.

    CAS  Article  PubMed  Google Scholar 

  14. Greer PB, Doorm TV. Evaluation of an algorithm for the assessment of the MTF using an edge method. Med Phys. 2000;27:2048–59.

    CAS  Article  PubMed  Google Scholar 

  15. Medical diagnostic X-ray equipment—radiation conditions for use in the determination of characteristics. IEC Standard 61267;1994.

  16. Medical electrical equipment—characteristics of digital X-ray imaging devices—part 1: Determination of the detective quantum efficiency. IEC Standard 62220-1;2003.

  17. Dobbins III JT. Image quality metrics for digital systems. In: Beutel J, Kundel HL, Van Meter RL, editors. Handbook of medical imaging. Vol. 1: SPIE Press; 2000. p. 161–222.

  18. Evaluation and routine testing in medical imaging departments—part 3-3: acceptance tests—imaging performance of X-ray equipment for digital subtraction angiography (DSA). IEC Standard 61223-3-3;1996.

Download references

Acknowledgments

The authors thank Kazuhiro Iinuma and Hiroshi Sasaki of the International University of Health and Welfare for their insightful suggestions. The authors are also grateful to Akihito Takahashi, Naotaka Sato, Shingo Abe, Hisanori Kato, Naoko Kuratomi, and Kae Aoki of the Toshiba Medical Systems Corporation for their cooperation in making valuable data available for this study. We wish to express our sincere thanks to the reviewers and the editors of this journal for their great support.

Author information

Affiliations

  1. Toshiba Medical Systems Corporation, 1385 Shimoishigami, Otawara, Tochigi, 324-8550, Japan

    Masayuki Nishiki, Takuya Sakaguchi & Kyojiro Nambu

  2. Toshiba Medical Systems Engineering Co., Ltd., 1385 Shimoishigami, Otawara, Tochigi, 324-8550, Japan

    Kunio Shiraishi

  3. Division of Radiological Sciences, International University of Health and Welfare Graduate School, 2600-1 Kita-Kanemaru, Otawara, Tochigi, 324-8501, Japan

    Masayuki Nishiki

Authors
  1. Masayuki Nishiki
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kunio Shiraishi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Takuya Sakaguchi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Kyojiro Nambu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Masayuki Nishiki.

About this article

Cite this article

Nishiki, M., Shiraishi, K., Sakaguchi, T. et al. Method for reducing noise in X-ray images by averaging pixels based on the normalized difference with the relevant pixel. Radiol Phys Technol 1, 188–195 (2008). https://doi.org/10.1007/s12194-008-0028-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12194-008-0028-z

Keywords

  • Noise
  • Noise reduction
  • Digital image processing