Skip to main content

Advertisement

Log in

Enhancement of the ultrasound images by modified anisotropic diffusion method

  • Original Article
  • Published:
Medical & Biological Engineering & Computing Aims and scope Submit manuscript

Abstract

Speckle is a primary factor which degrades the contrast resolution and masks the meaningful texture information present in an ultrasound image. Its presence severely hampers the interpretation and analysis of ultrasound images. When speckle reduction technique is applied for visual enhancement of ultrasound images, it is to be kept in mind that blurring associated with speckle reduction should be less and fine details are properly enhanced. With these points in consideration, the modified speckle reduction anisotropic diffusion (MSRAD) method is proposed in the present study to improve the visual quality of the ultrasound images. In the proposed MSRAD method, the four neighboring pixel template in speckle reduction anisotropic diffusion (SRAD) method of Yu and Acton (IEEE Trans Image Process 11:1260–1270, 2002) have been replaced by a new template of larger number of neighboring pixels to calculate the diffusion term. To enhance visual quality of ultrasound images, nonquadratic regularization (Yu and Yadegar, Proceedings of the IEEE international conference on image processing, 2006) is incorporated with MSRAD method and accordingly changes in parameter settings have been made. The performance of MSRAD method was evaluated using clinical ultrasound images, interpretation by the medical experts and results of MSRAD method by subjective and objective criteria.

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

Access this article

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

Similar content being viewed by others

References

  1. Abbott JG, Thurstone FL (1979) Acoustic speckle: theory and experimental analysis. Ultrason Imaging 1:303–324

    Article  CAS  PubMed  Google Scholar 

  2. Abd-Elmoniem KZ, Kadah YM, Youssef AM (2000) Real time adaptive ultrasound speckle reduction and coherence enhancement. In: International conference on image processing. Vancouver, Canada

  3. Abd-Elmoniem KZ, Youssef A-BM, Kadah YM (2002) Real-time speckle reduction and coherence enhancement in ultrasound imaging via nonlinear anisotropic diffusion. IEEE Trans Biomed Eng 49(9):997–1014

    Article  PubMed  Google Scholar 

  4. Acton ST (2005) Deconvolutional speckle reducing anisotropic diffusion. In: Proceedings of the IEEE international conference on image processing. Charlottesville, USA

  5. Aja-Fernandez S, Alberola-Lopez C (2006) On the estimation of the coefficient of variation for anisotropic diffusion speckle filtering. IEEE Trans Image Process 15(9):2694–2701

    Article  PubMed  Google Scholar 

  6. Badawi AM (2007) Scatterer density in nonlinear diffusion for speckle reduction in ultrasound imaging: the isotropic case. Int J Biol Biomed Med Sci 3:149–167

    Google Scholar 

  7. Badawi AM, Rushdi MA (2006) Speckle reduction in medical ultrasound: a novel scatterer density weighted nonlinear diffusion algorithm implemented as a neural-network filter. In: Proceedings of the IEEE international conference on engineering in medicine and biology society. New York, USA

  8. Binh NT, Thanh NC (2007) Object detection of speckle image base on curvelet transform. ARPN J Eng Appl Sci 2(3):14–16

    Google Scholar 

  9. Black MJ, Sapiro G, Marimont DH, Hegger D (1998) Robust anisotropic diffusion. IEEE Trans Image Process 7(3):421–432

    Article  CAS  PubMed  Google Scholar 

  10. Brownrigg DRK (1984) The weighted median filter. Commun Assoc Comput Mach 27:204–208

    Google Scholar 

  11. Chen Y, Yin R, Flynn P, Broschat S (2003) Aggressive region growing for speckle reduction in ultrasound images. Pattern Recogn Lett 24:677–691

    Article  Google Scholar 

  12. Frost VS, Stiles JA, Shanmugan KS, Holtzman JC (1982) A model for radar images and its application to adaptive digital filtering of multiplicative noise. IEEE Trans Pattern Anal Mach Intell PAMI-4: 157–165

    Google Scholar 

  13. Gerig G, Kubler O, Kikinis R, Jolesz FA (1992) Nonlinear anisotropic filtering of MRI data. IEEE Trans Med Imaging 11(2):221–232

    Google Scholar 

  14. Gupta S, Chauhan RC, Sexana SC (2004) Wavelet-based statistical approach for speckle reduction in medical ultrasound images. Med Bio Eng Comput 42(2):189–192

    Article  CAS  Google Scholar 

  15. Kim YS, Ra JB (2005) Improvement of ultrasound image based on wavelet transform: speckle reduction and edge enhancement. In: Proceedings of SPIE, vol 5747. Bellingham, WA

  16. Kim HS, Yoo JM, Park MS, Dinh TN, Lee GS (2007) An anisotropic diffusion based on diagonal edges. In: the 9th international conference on advanced communication technology, pp 384–388

  17. Kim HS, Yoon HS, Toan ND, Lee GS (2008) Anisotropic diffusion transform based on directions of edges. In: Proceedings of the IEEE international conference on computer and information technology workshops. Washington, USA, pp 386–400

  18. Krissian K, Westin C-F, Kikinis R, Vosburgh KG (2007) Oriented speckle reducing anisotropic diffusion. IEEE Trans Image Process 16(5):1412–1424

    Article  PubMed  Google Scholar 

  19. Kuan DT, Sawchuk AA, Strand TC, Chavel P (1987) Adaptive restoration of image with speckle. IEEE Trans Acoust Speech Signal Process ASSP 35:373–383

    Article  Google Scholar 

  20. Lee JS (1986) Speckle suppression and analysis for synthetic aperture radar. Opt Eng 25:636–643

    Google Scholar 

  21. Loizou CP, Pattichis CS, Pantziaris M, Tyllis T, Nicolaides A (2006) Quality evaluation of ultrasound imaging in the carotid artery based on normalization and speckle reduction filtering. Med Biol Eng Comput 44(5):414–426

    Article  CAS  PubMed  Google Scholar 

  22. Ma J, Plonka G (2007) Combined curvelet shrinkage and nonlinear anisotropic diffusion. IEEE Trans Image Process 16(9):2198–2206

    Article  PubMed  Google Scholar 

  23. Maalouf A, Carré P, Augereau B, Fernandez-Maloigne C (2007) Bandelet-based anisotropic diffusion. In: Proceedings of the IEEE international conference on image processing, pp 289-292

  24. Perona P, Malik J (1990) Scale space and edge detection using anisotropic diffusion. IEEE Trans Pattern Anal Mach Intell 12:629–639

    Article  Google Scholar 

  25. Pratt WK (1977) Digital image processing. Wiley, New York

    Google Scholar 

  26. Rabbani H, Vafadust M, Abolmaesumi P, Gazor S (2008) Speckle noise reduction of medical ultrasound images in complex wavelet domain using mixture priors. IEEE Trans Biomed Eng 55(9):2152–2160

    Article  PubMed  Google Scholar 

  27. Rajan J, Kaimal MR (2006) Image denoising using wavelet embedded anisotropic diffusion (WEAD). In: Proceedings of the IEEE international conference on visual information engineering, pp 589–593

  28. Saad AS (2006) Speckle reduction of ultrasound images using wavelets analysis. IMIBE, Germany, pp 51–54

  29. Sattar F, Floreby L, Salomonsson G, Lovstrom B (1997) Image enhancement based on a nonlinear multiscale method. IEEE Trans Image Process 6(6):888–895

    Article  CAS  PubMed  Google Scholar 

  30. Song X-Y, Zhang S, Song K-O, Yang W, Chen Y-Z (2008) Speckle supression for medical ultrasound images based on modelling speckle with rayleigh distribution in contourlet domain. In: Proceedings of the international conference on wavelet analysis and pattern recognition. Hong Kong, pp 194–199

  31. Tauber C, Batatia H, Ayache A (2004) A robust speckle reduction anisotropic diffusion. In: Proceedings of the IEEE international conference on image processing, pp 247–250

  32. Thakur A, Anand R (2005) Image quality based comparative evaluation of wavelet filters in ultrasound speckle reduction. Dig Sig Process 15(5):455–465

    Article  Google Scholar 

  33. Wang Z, Bovik A (2002) A universal quality index. IEEE Signal Proc Lett 9(3):81–84

    Article  CAS  Google Scholar 

  34. Wang B, Liu DC (2008) A novel edge enhancement method for ultrasound imaging. In: Proceedings of the IEEE international conference on bioinformatics, biomedical engineering. Shanghai, China, pp 2414–2417

  35. Weickert J (1997) A review of nonlinear diffusion filtering. In: ter Haar Romeny BM, Florack L, Koederink J, Viergever M (eds) Lecture notes in computer science, scale-space theory in computer vision, vol 1252. Springer-Verlag, Germany; Berlin, pp 3–28

  36. Xie J, Jiang YF, Tsui HT, Heng PA (2006) Boundary enhancement and speckle reduction for ultrasound images via salient structure extraction. IEEE Trans Biomed Eng 53:2300–2309

    Article  PubMed  Google Scholar 

  37. Yang Z, Fox MD (2004) Speckle reduction and structure enhancement by multichannel median boosted anisotropic diffusion. EURASIP J App Sig Process 16:2492–2502

    Article  Google Scholar 

  38. Yu Y, Acton ST (2002) Speckle reducing anisotropic diffusion. IEEE Trans Image Process 11:1260–1270

    Article  PubMed  Google Scholar 

  39. Yu Y, Acton ST (2004) Edge detection in ultrasound imagery using the instantaneous coefficient of variation. IEEE Trans Image Process 13(12):1640–1655

    Article  PubMed  Google Scholar 

  40. Yu Y, Yadegar J (2006) Regularized speckle reducing anisotropic diffusion for feature characterization. In: Proceedings of the IEEE international conference on image processing. CA: Los Angeles, pp 1577–1580

  41. Yu Y, Molloy JA, Acton ST (2004) Generalized speckle reducing anisotropic diffusion for ultrasound imagery. In: Proceedings of the 17th IEEE symposium on computer-based medical system. Bethesda, Maryland, pp 279–284

  42. Yue Y, Croitoru MM, Bidani A, Zwischenberger JB, Clark JW (2005) Ultrasound speckle suppression and edge enhancement using multiscale nonlinear wavelet diffusion. In: Proceedings of the IEEE international conference on engineering in medicine and biology society. Shanghai, China, pp 6429–6432

  43. Yue Y, Croitoru MM, Bidani A, Zwischenberger JB, Clark JW (2006) Nonlinear multiscale wavelet diffusion for speckle suppression and edge enhancement in ultrasound images. IEEE Trans Med Imaging 25(3):297–311

    Article  PubMed  Google Scholar 

  44. Zhang F, Yoo YM, Zhang L, Koh LM, Kim Y (2006) Multiscale nonlinear diffusion and shock filter for ultrasound image enhancement. In: Proceedings of the 2006 IEEE computer society conference on computer vision and pattern recognition, pp 1972–1977

  45. Zhang F, Yoo YM, Koh LM, Kim Y (2007) Nonlinear diffusion in Laplacian pyramid domain for ultrasonic speckle reduction. IEEE Trans Med Imaging 26(2):200–211

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

The authors wish to acknowledge the Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee and the Department of Radiodiagnosis and Imaging, Postgraduate Institute of Medical Education and Research, Chandigarh for their constant patronage and support in carrying out the research work.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Deepti Mittal.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Mittal, D., Kumar, V., Saxena, S.C. et al. Enhancement of the ultrasound images by modified anisotropic diffusion method. Med Biol Eng Comput 48, 1281–1291 (2010). https://doi.org/10.1007/s11517-010-0650-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11517-010-0650-x

Keywords

Navigation