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Analysis of Speckle Pattern Quality and Uncertainty for Cardiac Strain Measurements Using 3D Digital Image Correlation

  • Paolo FerraiuoliEmail author
  • John W. Fenner
  • Andrew J. Narracott
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 27)

Abstract

Measurement of full-field cardiac strain using optical methods has potential application to validate ultrasound measurements ex vivo, confirming their suitability for accurate in vivo strain imaging. This study describes the use of an effective technique to create a speckle pattern over the surface of a porcine heart for ex vivo experiments with the 3D digital image correlation (DIC) method. We characterised the quality of the speckle pattern applied on the cardiac surface by analysis of speckle size and evaluated the baseline uncertainty of 3D-DIC technique using a zero-strain test, applying rigid-body motion to position the marked sample at four locations. Strain errors were reported at a high spatial resolution (~128 µm) and were evaluated over a range of subset sizes. For subset size greater than 29 pixels the strain error was less than 1% making the baseline uncertainty of the 3D-DIC system acceptable to measure strains on the cardiac surface of the order 10%.

Keywords

Digital image correlation Speckle pattern Zero-strain test Cardiac imaging Soft tissues 

Notes

Acknowledgments

This work is funded by the European Commission through the H2020 Marie Skłodowska-Curie VPH-CaSE Training Network (www.vph-case.eu), GA No. 642612.

References

  1. 1.
    Townsend, N., Wilson, L., Bhatnagar, P., Wickramasinghe, K., Rayner, M., Nichols, M.: Cardiovascular disease in Europe: epidemiological update 2016. Eur. Heart J. 37(42), 3232–3245 (2016)CrossRefGoogle Scholar
  2. 2.
    Dandel, M., Lehmkuhl, H., Knosalla, C., Suramelashvili, N., Hetzer, R.: Strain and strain rate imaging by echocardiography - basic concepts and clinical applicability. Curr. Cardiol. Rev. 5(2), 133–148 (2009)CrossRefGoogle Scholar
  3. 3.
    Zhang, H., Iijima, K., Huang, J., Walcott, G.P., Rogers, J.M.: Optical mapping of membrane potential and epicardial deformation in beating hearts. Biophys. J. 111(2), 438–451 (2016)CrossRefGoogle Scholar
  4. 4.
    Palanca, M., Tozzi, G., Cristofolini, L.: The use of digital image correlation in the biomechanical area: a review. Int. Biomech. 3(1), 1–21 (2016)CrossRefGoogle Scholar
  5. 5.
    Sutton, M.A., Orteu, J.-J., Schreier, H.: Image Correlation for Shape, Motion and Deformation Measurements. Springer, Boston (2009)Google Scholar
  6. 6.
    Lecompte, D., Smits, A., Bossuyt, S., Sol, H., Vantomme, J., Van Hemelrijck, D., Habraken, A.M.: Quality assessment of speckle patterns for digital image correlation. Opt. Lasers Eng. 44(11), 1132–1145 (2006)CrossRefGoogle Scholar
  7. 7.
    Crammond, G., Boyd, S.W., Dulieu-Barton, J.M.: Speckle pattern quality assessment for digital image correlation. Opt. Lasers Eng. 51(12), 1368–1378 (2013)CrossRefGoogle Scholar
  8. 8.
    Pan, B., Lu, Z., Xie, H.: Mean intensity gradient: An effective global parameter for quality assessment of the speckle patterns used in digital image correlation. Opt. Lasers Eng. 48(4), 469–477 (2010)CrossRefGoogle Scholar
  9. 9.
    Hua, T., Xie, H., Wang, S., Hu, Z., Chen, P., Zhang, Q.: Evaluation of the quality of a speckle pattern in the digital image correlation method by mean subset fluctuation. Opt. Laser Technol. 43(1), 9–13 (2011)CrossRefGoogle Scholar
  10. 10.
    Hokka, M., Mirow, N., Nagel, H., Irqsusi, M., Vogt, S., Kuokkala, V.: In-vivo deformation measurements of the human heart by 3D digital image correlation. J. Biomech. 48(10), 2217–2220 (2015)CrossRefGoogle Scholar
  11. 11.
    Petterson, N.J., Pennings, K.A.M.A., Van Tuijl, S., Rutten, M.C.M., Van De Vosse, F.N., Lopata, R.G.P.: Semi-3D strain imaging in normal and LVAD supported ex vivo beating hearts (2015)Google Scholar
  12. 12.
    Azhari, H., Weiss, J.L., Rogers, W.J., Siu, C., Zerhouni, A., Shapiro, E.P.: Noninvasive quantification of principal strains in normal canine hearts using tagged MRI images in 3-D. Am. J. Physiol. Hear. Circ. Physiol. 264(1), 205–216 (1993)Google Scholar
  13. 13.
    Hashima, A.R., Young, A.A., McCulloch, A.D., Waldman, L.K.: Nonhomogeneous analysis of epicardial strain distributions during acute myocardial ischemia in the dog. J. Biomech. 26(1), 19–35 (1993)CrossRefGoogle Scholar
  14. 14.
    Lionello, G., Sirieix, C., Baleani, M.: An effective procedure to create a speckle pattern on biological soft tissue for digital image correlation measurements. J. Mech. Behav. Biomed. Mater. 39, 1–8 (2014)CrossRefGoogle Scholar
  15. 15.
    Luyckx, T., Verstraete, M., De Roo, K., De Waele, W., Bellemans, J., Victor, J.: Digital image correlation as a tool for three-dimensional strain analysis in human tendon tissue. J. Exp. Orthop. 1(1), 7 (2014)CrossRefGoogle Scholar
  16. 16.
    Robert, L., Nazaret, F., Cutard, T., Orteu, J.-J.: Use of 3-D digital image correlation to characterize the mechanical behavior of a fiber reinforced refractory castable. Exp. Mech. 47(6), 761–773 (2007)CrossRefGoogle Scholar
  17. 17.
    Otsu, N.: A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man. Cybern. 9(1), 62–66 (1979)CrossRefMathSciNetGoogle Scholar
  18. 18.
    Blaber, J., Adair, B., Antoniou, A.: Ncorr: open-source 2D digital image correlation Matlab software. Exp. Mech. 55(6), 1105–1122 (2015)CrossRefGoogle Scholar
  19. 19.
    Genovese, K., Lee, Y.U., Humphrey, J.D.: Novel optical system for in vitro quantification of full surface strain fields in small arteries: I. Theory and design. Comput. Methods Biomech. Biomed. Eng. 14(3), 213–225 (2011)CrossRefGoogle Scholar
  20. 20.
    Berfield, T.A., Patel, J.K., Shimmin, R.G., Braun, P.V., Lambros, J., Sottos, N.R.: Micro- and nanoscale deformation measurement of surface and internal planes via digital image correlation, pp. 51–62 (2007)Google Scholar
  21. 21.
    Waldman, L.K., Fung, Y.C., Covell, J.W.: Transmural myocardial deformation in the canine left ventricle. Normal in vivo three-dimensional finite strains. Circ. Res. 57(1), 152–163 (1985)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Paolo Ferraiuoli
    • 1
    • 2
    Email author
  • John W. Fenner
    • 1
    • 2
  • Andrew J. Narracott
    • 1
    • 2
  1. 1.Mathematical Modelling in Medicine Group, Department of Infection, Immunity and Cardiovascular DiseaseUniversity of SheffieldSheffieldUK
  2. 2.Insigneo Institute for in Silico MedicineUniversity of SheffieldSheffieldUK

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