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High dynamic range ultrasound imaging

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

High dynamic range (HDR) imaging is a popular computational photography technique that has found its way into every modern smartphone and camera. In HDR imaging, images acquired at different exposures are combined to increase the luminance range of the final image, thereby extending the limited dynamic range of the camera. Ultrasound imaging suffers from limited dynamic range as well; at higher power levels, the hyperechogenic tissue is overexposed, whereas at lower power levels, hypoechogenic tissue details are not visible. In this work, we apply HDR techniques to ultrasound imaging, where we combine ultrasound images acquired at different power levels to improve the level of detail visible in the final image.

Methods

Ultrasound images of ex vivo and in vivo tissue are acquired at different acoustic power levels and then combined to generate HDR ultrasound (HDR-US) images. The performance of five tone mapping operators is quantitatively evaluated using a similarity metric to determine the most suitable mapping for HDR-US imaging.

Results

The ex vivo and in vivo results demonstrated that HDR-US imaging enables visualizing both hyper- and hypoechogenic tissue at once in a single image. The Durand tone mapping operator preserved the most amount of detail across the dynamic range.

Conclusions

Our results strongly suggest that HDR-US imaging can improve the utility of ultrasound in image-based diagnosis and procedure guidance.

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References

  1. Banterle F, Artusi A, Debattista K, Chalmers A (2011) Advanced high dynamic range imaging: theory and Practice. AK Peters (CRC Press), Natick

    Book  Google Scholar 

  2. Cincotti G, Loi G, Pappalardo M (2001) Frequency decomposition and compounding of ultrasound medical images with wavelet packets. IEEE Trans Med Imaging 20(8):764–771

    Article  PubMed  CAS  Google Scholar 

  3. Coupé P, Hellier P, Kervrann C, Barillot C (2009) Nonlocal means-based speckle filtering for ultrasound images. IEEE Trans Image Process 18(10):2221–2229

    Article  PubMed  PubMed Central  Google Scholar 

  4. Debevec P.E, Malik J (1997) Recovering high dynamic range radiance maps from photographs. In: Proceedings of the 24th annual conference on computer graphics and interactive techniques, SIGGRAPH ’97. ACM Press/Addison-Wesley Publishing Co., New York, NY, USA, pp 369–378

  5. Durand F, Dorsey J (2002) Fast bilateral filtering for the display of high-dynamic-range images. In: Proceedings of the 29th annual conference on computer graphics and interactive techniques, SIGGRAPH ’02. ACM, New York, NY, USA, pp 257–266

  6. Erez Y, Schechner YY, Adam D (2006) Ultrasound image denoising by spatially varying frequency compounding. Pattern recognition: 28th DAGM symposium. Berlin, Germany, 12–14 September, 2006. Springer, Berlin Heidelberg, pp 1–10

  7. Huang J, Triedman JK, Vasilyev NV, Suematsu Y, Cleveland RO, Dupont PE (2007) Imaging artifacts of medical instruments in ultrasound-guided interventions. J Ultrasound Med 26(10):1303–1322

    Article  PubMed  Google Scholar 

  8. Hung AH, Liang T, Sukerkar PA, Meade TJ (2013) High dynamic range processing for magnetic resonance imaging. PLoS ONE 8(11):1–11

    Google Scholar 

  9. Perperidis A (2016) Postprocessing approaches for the improvement of cardiac ultrasound B-mode images: a review. IEEE Trans Ultrason Ferroelectr Freq Control 63(3):470–485

    Article  PubMed  Google Scholar 

  10. Pizer SM, Amburn EP, Austin JD, Cromartie R, Geselowitz A, Greer T, Romeny BTH, Zimmerman JB (1987) Adaptive histogram equalization and its variations. Comput Vis Graph Image Process 39(3):355–368

    Article  Google Scholar 

  11. Prince JL, Links J (2014) Medical imaging signals and systems, 2nd edn. Pearson, New York

    Google Scholar 

  12. Reinhard E, Kunkel T, Marion Y, Brouillat J, Cozot R, Bouatouch K (2007) Image display algorithms for high- and low-dynamic-range display devices. J Soc Inf Display 15(12):997–1014

    Article  Google Scholar 

  13. Reinhard E, Stark M, Shirley P, Ferwerda J (2002) Photographic tone reproduction for digital images. In: Proceedings of the 29th annual conference on computer graphics and interactive techniques, SIGGRAPH ’02. ACM, New York, NY, USA, pp 267–276

  14. Ren H, Anuraj B, Dupont PE (2017) Varying ultrasound power level to distinguish surgical instruments and tissue. Med Biol Eng Comput 56(3), 453–467. https://doi.org/10.1007/s11517-017-1695-x

  15. Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600–612

    Article  PubMed  Google Scholar 

  16. Ward G (2003) Fast, robust image registration for compositing high dynamic range photographs from hand-held exposures. J Graph Tools 8(2):17–30

    Article  Google Scholar 

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Acknowledgements

The authors would like to thank Neil Tenenholtz, Ph.D. for insightful discussions, and Yashraj Narang, Richard Nuckols, Ph.D. and Mohsen Moradi Dalvand, Ph.D. for their help with data collection.

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Corresponding authors

Correspondence to Alperen Degirmenci or Robert D. Howe.

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Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Additional information

This work was supported by the US National Institutes of Health under Grant NIH 1R21EB018938, Toyota Motor North America Inc., and the NVIDIA Corporation Academic Hardware Grant Program.

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Degirmenci, A., Perrin, D.P. & Howe, R.D. High dynamic range ultrasound imaging. Int J CARS 13, 721–729 (2018). https://doi.org/10.1007/s11548-018-1729-3

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  • DOI: https://doi.org/10.1007/s11548-018-1729-3

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