Robust Bone Detection in Ultrasound Using Combined Strain Imaging and Envelope Signal Power Detection

  • Mohammad Arafat Hussain
  • Antony Hodgson
  • Rafeef Abugharbieh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8673)


Bone localization in ultrasound (US) remains challenging despite encouraging advances. Current methods, e.g. local image phase-based feature analysis, showed promising results but remain reliant on delicate parameter selection processes and prone to errors at confounding soft tissue interfaces of similar appearance to bone interfaces. We propose a different approach combining US strain imaging and envelope power detection at each radio-frequency (RF) sample. After initial estimation of strain and envelope power maps, we modify their dynamic ranges into a modified strain map (MSM) and a modified envelope map (MEM) that we subsequently fuse into a single combined map that we show corresponds robustly to actual bone boundaries. Our quantitative results demonstrate a marked reduction in false positive responses at soft tissue interfaces and an increase in bone delineation accuracy. Comparisons to the state-of-the-art on a finite-element-modelling (FEM) phantom and fiducial-based experimental phantom show an average improvement in mean absolute error (MAE) between actual and estimated bone boundaries of 32% and 14%, respectively. We also demonstrate an average reduction in false bone responses of 87% and 56%, respectively. Finally, we qualitatively validate on clinical in vivo data of the human radius and ulna bones, and demonstrate similar improvements to those observed on phantoms.


Ultrasound bone strain imaging segmentation 


  1. 1.
    Hacihaliloglu, I., Abugharbieh, R., Hodgson, A.J., Rohling, R.N.: Bone Segmentation and Fracture Detection in Ultrasound Using 3D Local Phase Features. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds.) MICCAI 2008, Part I. LNCS, vol. 5241, pp. 287–295. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  2. 2.
    Hacihaliloglu, I., Abugharbieh, R., Hodgson, A.J., Rohling, R.N.: Automatic Adaptive Parameterization in Local Phase Feature-based Bone Segmentation in Ultrasound. Ultrasound in Med. and Biol. 37(10), 1689–1703 (2011)Google Scholar
  3. 3.
    Hussain, M.A., Anas, E.M.A., Alam, S.K., Lee, S.Y., Hasan, M.K.: Direct and Gradient Based Average Strain Estimation by Using Weighted Nearest Neighbor Cross-correlation Peaks. IEEE Trans. Ultra. Ferro. Freq. Cont. 59(8), 1713–1728 (2012)CrossRefGoogle Scholar
  4. 4.
    Wen, X., Salcudean, S.E.: Enhancement of Bone Surface Visualization Using Ultrasound Radio-frequency Signals. In: IEEE Ultra. Symp., vol. 1051, pp. 2535–2538 (2007)Google Scholar
  5. 5.
    Rivaz, H., Boctor, E.M., Choti, M.A., Hager, G.D.: Real-time Regularized Ultrasound Elastography. IEEE Trans. Med. Imag. 30(4), 928–945 (2011)CrossRefGoogle Scholar
  6. 6.
    Lindop, J.E., Treece, G.M., Gee, A.H., Prager, R.W.: Estimation of Displacement Location for Enhanced Strain Imaging. IEEE Trans. Ultra. Ferro. Freq. Cont. 54(9), 1751–1771 (2007)CrossRefGoogle Scholar
  7. 7.
    Hussain, M.A., Alam, S.K., Lee, S.Y., Hasan, M.K.: A Robust Strain Estimation Algorithm Using Combined Radio-frequency and Envelope Cross-correlation with Diffusion Filtering. Ultrason. Imag. 34(2), 93–109 (2012)CrossRefGoogle Scholar
  8. 8.
    Jensen, J.A.: Field: A Program for Simulating Ultrasound Systems. In: 10th Nordicbaltic Conf. on Biomed. Imag. Part I, vol. 4(1), pp. 351–353 (1996)Google Scholar
  9. 9.
    Pistoia, W., Rietbergen, B.V., Lochm\(\ddot{u}\)ller, E., Lill, C.A., Eckstein, F., R\(\ddot{u}\)egsegger, P.: Estimation of Distal Radius Failure Load With Micro-Finite Element Analysis Models Based on Three-dimensional Peripheral Quantitative Computed Tomography Images. Bone 30(6), 842–848 (2002)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Mohammad Arafat Hussain
    • 1
  • Antony Hodgson
    • 2
  • Rafeef Abugharbieh
    • 1
  1. 1.Department of Electrical and Computer EngineeringThe University of British ColumbiaVancouverCanada
  2. 2.Department of Mechanical EngineeringThe University of British ColumbiaVancouverCanada

Personalised recommendations