MATEC Web Conf.
Volume 74, 2016The 3rd International Conference on Mechanical Engineering Research (ICMER 2015)
|Number of page(s)||4|
|Published online||29 August 2016|
- Guillaume Picinbono, Herve Delingette, Nicholas Ayache. Non-linear anisotropic elasticity for real-time surgery simulation. Graphical Models 65 (2003) 305–321 [CrossRef]
- Victoria Valinluck Lao, Scott R. Steele. The role of simulation in colon and rectal surgery training. Seminars in Colon and Rectal Surgery, In Press, Accepted Manuscript, Available online 14 April 2015
- Hsiu-Hsia Lin, Lun-Jou Lo. Three-dimensional computer-assisted surgical simulation and intraoperative navigation in orthognathic surgery: A literature review. Journal of the Formosan Medical Association, 114 (4) 2015, 300–307 [CrossRef]
- N. Abe, S. Kuroda, M. Furutani, E. Tanaka. Data-based prediction of soft tissue changes after orthognathic surgery: clinical assessment of new simulation software. International Journal of Oral and Maxillofacial Surgery, Volume 44 (1) 2015, 90–96 [CrossRef]
- Robert D. Acton. The Evolving Role of Simulation in Teaching Surgery in Undergraduate Medical Education. Surgical Clinics of North America, In Press, Corrected Proof, Available online 23 May 2015.
- Kwong Ming Tse, Long Bin Tan, Shu Jin Lee, Siak Piang Lim, Heow Pueh Lee. Investigation of the relationship between facial injuries and traumatic brain injuries using a realistic subject-specific finite element head model. Accident Analysis & Prevention, 79, 2015, 13–32. [CrossRef]
- Jennifer A. DeWit, Duane S. Cronin. Cervical spine segment finite element model for traumatic injury prediction. Journal of the Mechanical Behavior of Biomedical Materials, 10, June 2012, 138–150. [CrossRef]
- Lei Cheng, Blake Hannaford. Finite Element Analysis for evaluating liver tissue damage due to mechanical compression. Journal of Biomechanics, 48 (6) 2015, 948–955. [CrossRef]
- Skrinjar O Nabavi, A Duncan. Model driven brain shift compensation. Medical Image Analysis, 6(4), 2002. 361–373. [CrossRef]
- Warfield SK, F. Talos, et. al. Real time registration of volumetric brain MRI by biomechanical simulation of deformation during image guided neurosurgery. Computing and Visualization in Science, 5 (1), 2001, 3–11. [CrossRef]
- Ferrant M, Warrant SK, et al. Registration of 3D intraoperative MR images of the brain using a finite element biomechanical model. IEEE Transaction of medical Imaging, 20 (12), 2001, 1384 – 1397. [CrossRef]
- A. Mendizabal, I Aguinaga, E. Sanchez. Characterization and modelling of brain tissue for surgical simulation. Journal of the Mechanical behavior of Biomedical Materials 45, 2015, 1 – 10. [CrossRef]
- Sack Kaster, A. Samani. Measurement of the hyperelastic properties of ex vivo brain tissue slices. Journal of Biomechanics. 44 (6) 2011, 1158–1163 [CrossRef]
- C. Gao, K. Lister, J.P Desai. Constitutive modeling of liver tissue: experiment and theory. Annals of Biomedical Engineering 38 (2) 2010, 505–516. [CrossRef]
- R.J. Lapeer, P.D Gasson, V. Karri. A hyperelastic finite element model of human skin for interactive real time surgical simulation. IEEE Transactions of Biomedical Engineering 58 (4), 1013 – 1022. [CrossRef]
- J. Hug, R. Hutte, et. al. Virtual reality based simulation of endoscopic surgery. Presence: Teleoperat. Virtual Environment 9 (3), 2000, 310 – 333. [CrossRef]
- Pals Martin, Natal Jorge, AJM Ferreira. A comparative study of sevral material models for predictions of Hyperelastic properties: application to silicon rubber and soft tissues. Strain 42 (3), 2006, 135–147. [CrossRef] [EDP Sciences]
- Richard Moran, Joshua H Smith, Jose J. Garcia. Fitted hyperelastic parameters for human brain tissue from reported tension, compression and shear tests. Journal of Biomechanics. 47, 2014, 3762–3766. [CrossRef]
- A Yoshizawa, J. Okamoto, H Yamakawa, M.G. Fujie. Robot surgery based on the physical properties of the brain physical brain model for planning and navigation of a surgical robot. International conference on Robotics and Automation, April 2005. 904 – 911.
- Z. Liu, L. Bilston. On the viscoelastic character of a liver tissue. Experiment and modelling of the linear behavior. Biorheology 39 (6), 2000, 735 – 742.
- M. Sedef, E. Samur, C. Basdogan. Real time finite element simulation of linear viscoelastic tissue behavior based on experimental data. Computer Graphics and Applications, IEEE 26 (6) 2006, 28 – 38. [CrossRef]
- L Yoo, V Gupta, et al. Viscoelastic properties of bovine orbital connective tissue and fat: constitutive models. Biomechanics Model Mechanobiology. 8 (1), 2011, 901 – 914. [CrossRef]
- S. Misra, K. ramesh et al. Modeling of nonlinear elastic tissues for surgical simulation. Computational methods In Biomechanics. Biomedical engineering. 13 (6), 2010, 811–818. [CrossRef]
- B Ahn, J. Kim. Efficient soft tissue characterization under large deformation in medical simulations. International Journal of Precision Engineering Manufacturing. 10 (4), 2009, 115 – 121. [CrossRef]
- D. Brands, G. Peters, P. Bovendeerd. Design and numerical implementation of the brain tissue during impact. Journal of Biomechanics. 37(1), 2004, 127 – 134. [CrossRef]
- M Hrapko et al. The mechanical behavior of brain tissue: large strain response and constitutive modelling. Biorheology. 43(5), 2006, 623 – 636.
- L.E Bilston, Z. Liu, N. Phan Thien. Large strain behavior of brain tissue in shear. Some experimental data and differential constitutive model. Biorheology 38 (4) 2001, 335 – 345.
- Karol Miller, Adam Wittek, Grand Joldes. Biomechanics of the brain for computer-integrated surgery. Acta of Bioengineering and Biomechanics. 12 (2), 2010, 25–37
- T J Horgan, M D Gilchrist. The creation of three-dimensional finite element models for simulating head impact biomechanics. International Journal of Crash. 8(4), 2003, 353–366. [CrossRef]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.