Journal of the Korean Physical Society

, Volume 72, Issue 7, pp 811–817 | Cite as

Soft-compression Mammography Based on Weighted l1-norm Scatter Correction Scheme for Reducing Patient Pain during Breast Examination

  • Seokyoon Kang
  • Kyuseok Kim
  • Woosung Kim
  • Hyosung Cho
  • Changwoo Seo
  • Chulkyu Park
  • Dongyeon Lee
  • Soyoung Park
  • Guna Kim
  • Hyunwoo Lim
  • Hunwoo Lee
  • Jeongeun Park
  • Doohee Jean
  • Jieun Oh
Article
First Online:
Received:
Accepted:
  • 4 Downloads

Abstract

In mammography examination, compression of the breast is essential for reducing scattered X-rays and the radiation dose and for preventing motion artifacts, thereby producing optimal diagnostic breast images. However, mechanical compression of the breast often causes discomfort and pain during and after the examination and deters some patients from routine mammography screening. In this study, we propose a novel soft-compression mammography based on a weighted l1-norm scatter correction scheme in attempt to overcome these difficulties. We implemented the proposed algorithm and performed a simulation and experiment to demonstrate the feasibility of using the proposed method. According to our results, the structure of the breast phantom was much more clearly visible in the scatter-corrected image than in the original scatter-corrupted image. The contrast-to-noise ratio (CNR) for the scatter-corrected image was about 6.3, about 4.1 times larger than that for the scatter-corrupted image, indicating much improved image visibility. The proposed approach seems very promising for scatter correction in conventional mammography, thus allowing soft-compression breast examination in clinics.

Keywords

Soft compression Mammography Scatter correction Weighted l1-norm 
This is a preview of subscription content, log in to check access

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    J. Lewin, R. Hendrick, C. D’Orsi, P. Isaacs, L. Moss, A. Karellas, G. Sisney, C. Kuni and G. Cutter, Radiology 218, 873 (2001).CrossRefGoogle Scholar
  2. [2]
    S. Friedewald et al., JAMA 311, 2499 (2014).CrossRefGoogle Scholar
  3. [3]
    R. Saunders and E. Samei, Med. Phys. 35, 4464 (2008).CrossRefGoogle Scholar
  4. [4]
    W. Branderhorst, J. Groot, R. Highnam, A. Chan, M. Böhm-Vélez, M. Broeders, G. Heeten and C. Grimbergen, Eur. J. Radiol. 84, 596 (2015).CrossRefGoogle Scholar
  5. [5]
    M. Broeders, M. Voorde, W. Veldkamp, R. Engen, C. Landsveld, M. Jong, J. Win, K. Greve, E. Paap and G. Heeten, Eur. J. Radiol. 25, 821 (2015).CrossRefGoogle Scholar
  6. [6]
    B. Meng, H. Lee, L. Xing and B. Fahimian, Med. Phys. 40, 077907 (2013).CrossRefGoogle Scholar
  7. [7]
    C. Floyd, P. Beatty and C. Ravin, Invest. Radiol. 24, 30 (1989).CrossRefGoogle Scholar
  8. [8]
    K. Nykänen and S. Samuli, Med. Phys. 30, 1864 (2003).CrossRefGoogle Scholar
  9. [9]
    J. Ducote and S. Molloi, Phys. Med. Biol. 55, 1295 (2010).CrossRefGoogle Scholar
  10. [10]
    W. Zbijewski and F. Beekman, IEEE Trans. Med. Imaging 25, 817 (2006).CrossRefGoogle Scholar
  11. [11]
    J. Tarel and N. Hautière, In Proceeding of the IEEE International Conference on Computer Vision (ICCV) (Kyoto, Japan, Sept. 2009).Google Scholar
  12. [12]
    G. Meng et al., In Proceeding of the IEEE International Conference on Computer Vision (ICCV) (Sydney, Australia, Dec. 2013).Google Scholar
  13. [13]
    S. Boyd, N. Parikh, E. Chu, B. Peleato and J. Eckstein, Found. Trends in Mach. Learning 3, 1 (2011).CrossRefGoogle Scholar
  14. [14]
    C. Li, W. Segars, G. Tourassi, J. Boone and J. Dobbins, Med. Phys. 36, 3122 (2009).CrossRefGoogle Scholar
  15. [15]
    D. Erickson, J.Wells, G. Sturgeon, E. Samei, J. Dobbins, W. Segars and J. Lo, Med. Phys. 43, 23 (2016).CrossRefGoogle Scholar
  16. [16]
    G. Surgeon, N. Kiarashi, J. Lo, E. Samei and W. Segars, Med. Phys. 43, 2207 (2016).CrossRefGoogle Scholar
  17. [17]
    S. Leon, L. Brateman and L. Wagner, Med. Phys. 41, 111914 (2014).CrossRefGoogle Scholar
  18. [18]
    J. Boone and J. Seibert, Med. Phys. 15, 721 (1988).CrossRefGoogle Scholar

Copyright information

© The Korean Physical Society 2018

Authors and Affiliations

  • Seokyoon Kang
    • 1
  • Kyuseok Kim
    • 1
  • Woosung Kim
    • 1
  • Hyosung Cho
    • 1
  • Changwoo Seo
    • 1
  • Chulkyu Park
    • 1
  • Dongyeon Lee
    • 1
  • Soyoung Park
    • 1
  • Guna Kim
    • 1
  • Hyunwoo Lim
    • 1
  • Hunwoo Lee
    • 1
  • Jeongeun Park
    • 1
  • Doohee Jean
    • 1
  • Jieun Oh
    • 2
  1. 1.Department of Radiation Convergence EngineeringYonsei UniversityWonjuKorea
  2. 2.Division of Convergence TechnologyNational Cancer CenterGoyangKorea

Personalised recommendations