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Calculus detection for ultrasonography using decorrelation of forward scattered wave

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Abstract

Purpose

The purpose of this paper is to propose a novel strategy to detect small calculi efficiently.

Methods

The proposed calculus detection strategy focuses on decorrelation of forward scattered waves caused by the failure of Born’s approximation. A calculus causes waveform changes of transmit pulses, resulting in a decrease in the cross-correlation coefficients calculated from IQ signals scattered near the calculus position. Therefore, we can detect calculi from the appearance of dips in correlation coefficients.

Results

When a calculus exists in a digital tissue map, sharp and deep dips in cross-correlation coefficients between acoustic IQ signals appear around the calculus. By contrast, no apparent dip exists when a tissue map contains no calculus. A scan line interval of 0.2 mm or less is appropriate for the conditions simulated in this paper, and the proper transmit focal range for the proposed method is at a calculus range.

Conclusion

These results imply that the proposed strategy can improve the efficiency of US devices for small calculus detection.

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References

  1. Özdemir H, Demir MK, Temizöz O, et al. Phase inversion harmonic imaging improves assessment of renal calculi: a comparison with fundamental gray-scale sonography. J Clin Ultrasound. 2008;36:16–9.

    Article  PubMed  Google Scholar 

  2. Fowler KAB, Locken JA, Duchesne JH, et al. US for detecting renal calculi with nonenhanced CT as a reference standard. Radiology. 2002;222:109–13.

    Article  PubMed  Google Scholar 

  3. Lamb PM, Perry NM, Vinnicombe SJ, et al. Correlation between ultrasound characteristics, mammographic findings and histological grade in patients with invasive ductal carcinoma of the breast. Clin Radiol. 2000;55:40–4.

    Article  CAS  PubMed  Google Scholar 

  4. Jacob D, Brombart JC, Muller C, et al. Analysis of the results of 137 subclinical breast lesions excisions. Value of ultrasonography in the early diagnosis of breast cancer. J Gynecol Obstet Biol Reprod (Paris). 1997;26:27–31.

    CAS  Google Scholar 

  5. Mahnken AH, Mühlenbruch G, Das M, et al. MDCT detection of mitral valve calcification: prevalence and clinical relevance compared with echocardiography. Am J Roentgenol. 2007;188:1264–9.

    Article  Google Scholar 

  6. Liu F, Coursey CA, Grahame-Clarke C, et al. Aortic valve calcification as an incidental finding at CT of the elderly: severity and location as predictors of aortic stenosis. Am J Roentgenol. 2006;186:342–9.

    Article  Google Scholar 

  7. Janetschek G, Putz A, Feichtinger H. Renal transitional cell carcinoma mimicking stone echoes. J Ultrasound Med. 1988;7:83–6.

    CAS  PubMed  Google Scholar 

  8. Roesel GC, Toepfer NJ, Battino BS, et al. A calcified papillary renal cell carcinoma masquerading as a renal pelvic calculus. Curr Urol. 2007;1:217–8.

    Article  Google Scholar 

  9. Finn HM, Johnson RS. Adaptive detection mode with threshold control as a function of spatially sampled clutter-level estimates. RCA Rev. 1968;29:414–65.

    Google Scholar 

  10. Hansen VG, Ward HR. Detection performance of the cell averaging LOG/CFAR receiver. IEEE Trans Aerosp Electron Syst. 1972;5:648–52.

    Article  Google Scholar 

  11. Zhu Y, Weight JP. Ultrasonic nondestructive evaluation of highly scattering materials using adaptive filtering and detection. IEEE Trans Ultrason Ferroelect Freq Control. 1994;41:26–33.

    Article  Google Scholar 

  12. Kamiyama N, Okamura Y, Kakee A, et al. Investigation of ultrasound image processing to improve perceptibility of microcalcifications. J Med Ultrasonics. 2008;35:97–105.

    Article  Google Scholar 

  13. Schmidt T, Hohl C, Haage P, et al. Diagnostic accuracy of phase-inversion tissue harmonic imaging versus fundamental B-mode sonography in the evaluation of focal lesions of the kidney. Am J Roentgenol. 2003;180:1639–47.

    Google Scholar 

  14. Rosen EL, Soo MS. Tissue harmonic imaging sonography of breast lesions improved margin analysis, conspicuity, and image quality compared to conventional ultrasound. Clin Imaging. 2001;25:379–84.

    Article  CAS  PubMed  Google Scholar 

  15. Krücker JF, Meyer CR, LeCarpentier GL, et al. 3D spatial compounding of ultrasound imaging using image-based nonrigid registration. Ultrasound Med Biol. 2000;26:1475–88.

    Article  PubMed  Google Scholar 

  16. Moskalik A, Carson PL, Meyer CR, et al. Registration of 3-dimensional compound ultrasound scans of the breast for refraction and motion correction. Ultrasound Med Biol. 1995;21:769–78.

    Article  CAS  PubMed  Google Scholar 

  17. Weinstein SP, Conant EF, Sehgal C. Technical advances in breast ultrasound imaging. Semin Ultrasound CT MR. 2006;27:273–83.

    Article  PubMed  Google Scholar 

  18. Hossack JA, Hayward G. Finite-element analysis of 1–3 composite transducers. IEEE Trans Ultrason Ferroelect Freq Control. 1991;38:618–29.

    Article  CAS  Google Scholar 

  19. Lerch R. Simulation of piezoelectric devices by two- and three-dimensional finite elements. IEEE Trans Ultrason Ferroelect Freq Control. 1990;37:233–47.

    Article  CAS  Google Scholar 

Download references

Acknowledgments

This work was partly supported by the Research and Development Committee Program of the Japan Society of Ultrasonics in Medicine and the Innovative Techno-Hub for Integrated Medical Bio-imaging Project of the Special Coordination Funds for Promoting Science and Technology from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan.

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Authors and Affiliations

  1. Graduate School of Informatics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto, 606-8501, Japan

    Hirofumi Taki, Takuya Sakamoto & Toru Sato

  2. Advanced Biomedical Engineering Research Unit, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto, 606-8501, Japan

    Makoto Yamakawa

  3. Graduate School of Medicine, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto, 606-8501, Japan

    Tsuyoshi Shiina

Authors
  1. Hirofumi Taki
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  2. Takuya Sakamoto
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  3. Makoto Yamakawa
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  4. Tsuyoshi Shiina
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  5. Toru Sato
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Corresponding author

Correspondence to Hirofumi Taki.

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Taki, H., Sakamoto, T., Yamakawa, M. et al. Calculus detection for ultrasonography using decorrelation of forward scattered wave. J Med Ultrasonics 37, 129–135 (2010). https://doi.org/10.1007/s10396-010-0265-8

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  • DOI: https://doi.org/10.1007/s10396-010-0265-8

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