Skip to main content

Advertisement

SpringerLink
Log in

A Novel Medical Image Quality Index

  • Published:
Journal of Digital Imaging Aims and scope Submit manuscript

Abstract

A novel medical image quality index using grey relational coefficient calculation is proposed in this study. Three medical modalities, DR, CT and MRI, using 30 or 60 images with a total of 120 images used for experimentation. These images were first compressed at ten different compression ratios (10 ∼ 100) using a medical image compression algorithm named JJ2000. Following that, the quality of the reconstructed images was evaluated using the grey relational coefficient calculation. The results were shown consistent with popular objective quality metrics. The impact of different image aspects on four grey relational coefficient methods were further tested. The results showed that these grey relational coefficients have different slopes but very high consistency for various image areas. Nagai’s grey relational coefficient was chosen in this study because of higher calculation speed and sensitivity. A comparison was also made between this method and other windows-based objective metrics for various window sizes. Studies found that the grey relational coefficient results are less sensitive to window size changes. The performance of this index is better than some windows-based objective metrics and can be used as an image quality index.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

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

Similar content being viewed by others

References

  1. Wang Z, Bovik AC: A universal image quality index. IEEE Signal Process Lett 9:81–84, 2002

    Article  CAS  Google Scholar 

  2. Wang Z, Bovik AC, Sheikh HR, Simoncelli EP: Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13:600–612, 2004

    Article  PubMed  Google Scholar 

  3. İsmail A, Bulent S, Khalid S: Statistical evaluation of image quality measures. J Electron Imaging 11:206–223, 2002

    Article  Google Scholar 

  4. Lubin J: In: Watson AB Ed. The use of psychophysical data and models in the analysis of display system performance. MIT Press, Cambridge, 1993. Chapter 13

    Google Scholar 

  5. Chen TJ, Chuang KS, Chiang YC, Chang JH, Liu RS: A statistical method for evaluation quality of medical images: a case study in bit discarding and image compression. Comput Med Imaging Graph 28:167–175, 2004

    Article  PubMed  Google Scholar 

  6. Ponomarenko N, Lukin V, Zelensky A, Egiazarian K, Carli M, Battisti F:TID 2008—a database for evaluation of full-reference visual quality assessment metrics. Adv Modern Radio Electron 10:30–45, 2009. Available at: http://www.ponomarenko.info/tid2008.htm

  7. Keelan BW, Urabe H: ISO 20462, A psychophysical image quality measurement method. Proc SPIE IS&T Electron Imaging 5294:181–189, 2004

    Article  Google Scholar 

  8. Brill MH, Lubin J, Wolin D: Perceptual scaling of quality metrics for hardcopy image evaluation. IS&T NIP 15:435–438, 1999

    Google Scholar 

  9. Chen TJ, Chuang KS, Chang JH, Shiao YH, Chuang CC: A blurring index for medical images. J Digit Imaging 19:118–125, 2006

    Article  PubMed  Google Scholar 

  10. Chen TJ, Chuang KS, Jay W, Chen SC, Hwang IM, Jan ML: A novel image quality index using Moran I statistics. Phys Med Biol 48:131–137, 2003

    Article  Google Scholar 

  11. Shiao YH, Chen TJ, Chuang KS, Lin CH, Chuang CC: Quality of compressed medical images. J Digit Imaging 20:149–159, 2007

    Article  PubMed  Google Scholar 

  12. Deng JL: Introduction to grey system theory. J Grey Syst 1:1–24, 1989

    Google Scholar 

  13. You ML, Wang CW, Yeh CK: The development of completed grey relational analysis toolbox via Matlab. J Grey Syst 9:57–64, 2006

    Google Scholar 

  14. Daisuke Y, Li GD, Masatake N: New grey relational analysis for finding the invariable structure and its applications. J Grey Syst 8:167–178, 2005

    Google Scholar 

  15. Cliff AD, Ord JK: Spatial process: models and applications. Pion, London, 1981

    Google Scholar 

  16. Kalyanpur A, Neklesa VP, Taylor CR, Daftary AR, Brink AR: Evaluation of JPEG and wavelet compression of body CT images for direct digital teleradiologic transmission. Radiology 217:772–779, 2000

    PubMed  CAS  Google Scholar 

Download references

Acknowledgements

This work was supported by a research grant: NSC 97-2314-B-471-001-MY2 from the National Science Council of Taiwan.

Author information

Authors and Affiliations

  1. Department of Dental Laboratory Technology, Shu-Zen College of Medicine and Management, Kaohsiung, Taiwan, Republic of China, 82144

    Sheng-Chieh Lin

  2. Department of Radiological Technology, Central Taiwan University of Science and Technology, Taichung, Taiwan, Republic of China

    You-Chen Lin

  3. Department of Medical Imaging and Radiology, Shu-Zen College of Medicine and Management, Luju Shiang, Kaohsiung, Taiwan, 82144

    Weng-Song Feng & Tzong-Jer Chen

  4. Department of Radiation Oncology, E-DA Hospital/I-Shou University, Kaohsiung, Taiwan, Republic of China

    Jia-Ming Wu

Authors
  1. Sheng-Chieh Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. You-Chen Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Weng-Song Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jia-Ming Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tzong-Jer Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tzong-Jer Chen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lin, SC., Lin, YC., Feng, WS. et al. A Novel Medical Image Quality Index. J Digit Imaging 24, 874–882 (2011). https://doi.org/10.1007/s10278-010-9353-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10278-010-9353-y

Keywords

Search

Navigation