Eugenia, V., Pablo, B., et al. (2009) Over estimation of liver fibrosis staging using transient elastography in patients with chronic hepatitis C and significant liver inflammation. International Medical Press, 1359-6535.
 Silver, D., Karnik, G. and Osinusi, A. (2013) Effect of HIV on liver fibrosis among HCV-infected African Americans.
 Wen, C., Jeng, Y.-M., et al. (2001) Young’s modulus of human liver and correlation with pathological findings. Department of Electrical Engineering, National Taiwan University, IEEE, Ultrasonics Symposium, 1233.
 Mauro, M.S., Juan, F.C., et al, (2007) Comparing optimization algorithms for young’s modulus reconstruction in ultrasound elastography. Mechanical Department Katholieke Universiteit, Leuven, IEEE Ultrasonics Symposium.
 Christoph, F.D., Carla, S. and Maciej, J. (2011) Ultrasound of the liver. European Course Book by University of Bologna, Department of Diagnostic Imaging, 2nd Medical Faculty of Warsaw Medical University.
 Yves, B., Marie, B., Vincent, Di M., Frederic, C., Felipe, A., Anne, C., Michel, V., Francois, B., Pierre, O., Christine, K. and Thierry, P. (1999) Liver fibrosis progression in human immunodeficiency virus and hepatitis C virus coinfected patients. The Multivirc Group Hepatology, 30.
 Ayman, K. and Samir, S. (2011) Data mining visualization to support biochemical markers for liver fibrosis in patients with chronic hepatitis C virus. International Journal of Artificial Intelligence and Expert Systems (IJAE), 2.
 Abdelfattah, M.A., Sanaa, O.A. and Ahmed, A.A. (2013) Diagnostic value of fibronectin discriminant score for predicting liver fibrosis stages in chronic hepatitis C virus patients. Annals of Hepatology, 12, 44-53.
 Xavier, F., Sergi, A. and Josep, M.L. (2002) Identification of chronic hepatitis c patients without hepatic fibrosis by a simple predictive model. American Association for the Study of Liver Diseases. Hepatology, 36.
 Yu, I., Hiroshi, E., Tadashi, Y. and Hiroyuki, H. (2009) A method of liver fibrosis estimation based on combination of Rayleigh distributions. Proceedings of Symposium on Ultrasonic Electronics, 30, pp. 343-344.
 Monica, L., Sergiu, N. and Cristian, V. (2007) Estimating the fibrosis stage in the human liver tissue using image processing methods on ultrasonographic images. Proceedings of the 3rd International Conference—EMMIT.
 Cannon, S., Browne, L. and Fagan, J. (2010) Assessment of the accuracy of an ultrasound elastography liver scanning system using a PVA-cryogel phantom with optimal acoustic and mechanical properties. Physics in Medicine and Biology, 55, 5965-5983.
 Sandrin, L., Oudry, J. and Bastard, C. (2011) Non-invasive assessment of liver fibrosis by vibration-controlled transient elastography (Fibroscan®).
 (2012) ABAQUS installation and licensing guide.
 Division of Engineering Brown University (2012) ABAQUS tutorial. EN175: Advanced mechanics of solids.
 Amalka, P. (2009) Digital image analysis of cells. Applications in 2D, 3D and time. Box 337, SE-75105 Uppsala, Sweden. Faculty of Science and Technology, Centre for Image Analysis, Uppsala University, Uppsala, Pinidiyaarachchi.
 Thomas, M.D. (2011) Fundamentals of biomedical image processing. Biomedical Engineering, Springer-Verlag, Berlin/Heidelberg.
 Zhang, D.S. and Dwayne, D.A. (2004) Applications of digital image correlation to biological tissues. Journal of Biomedical Optics, 9, 691-699.
 Su, C. and Anand, L. (2003) A new digital image correlation algorithm for whole field displacement measurement. Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge.
 Tong, W. (2005) An evaluation of digital image correlation criteria for strain mapping applications. Yale University, Department of Mechanical Engineering, New Haven, Blackwell Publishing Ltd., Strain, 167-175.
 Christoph, E., Robert, T. and Daniel, G. (2012) Digital image correlation and tracking with matlab.