Model-Based Identification of Anatomical Boundary Conditions in Living Tissues

详细信息    查看全文

• 作者：Igor Peterlik (20) (21) (23)
  Hadrien Courtecuisse (20) (21) (22)
  Christian Duriez (21)
  Stéphane Cotin (20) (21)
  
• 刊名：Lecture Notes in Computer Science
• 出版年：2014
• 出版时间：2014
• 年：2014
• 卷：8498
• 期：1
• 页码：196-205
• 参考文献：1. Ahmadian, H., Mottershead, J., Friswell, M.: Boundary condition identification by solving characteristic equations. J. of Sound and Vibration?247(5), 755-63 (2001) CrossRef
  2. Suzuki, A., Kamiya, K., Yasuda, K.: Identification technique for nonlinear boundary conditions of a circular plate. J. of Sound and Vibration?289(1-2), 130-47 (2006) CrossRef
  3. Ahmadian, H., Zamani, A.: Identification of nonlinear boundary effects using nonlinear normal modes. Mechanical Systems and Signal Processing?23(6), 2008-018 (2009); Special Issue: Inverse Problems
  4. Carter, T.J., Sermesant, M., Cash, D.M., Barratt, D.C., Tanner, C., Hawkes, D.J.: Application of soft tissue modelling to image-guided surgery. Medical Engineering & Physics?27(10), 893-09 (2005) CrossRef
  5. Ferrant, M., Nabavi, A., Macq, B., Jolesz, F.A., Kikinis, R., Warfield, S.K.: Registration of 3-D intraoperative MR images of the brain using a finite-element biomechanical model. IEEE Trans. on Medical Imaging?20(12), 1384-397 (2001) CrossRef
  6. Veress, A.I., Phatak, N., Weiss, J.A.: Deformable image registration with Hyperelastic Warping. In: Handbook of Biomedical Image Analysis, pp. 487-33 (2005)
  7. Brock, K.K., Sharpe, M.B., Dawson, L.A., Kim, S.M., Jaffray, D.A.: Accuracy of finite element model-based multi-organ deformable image registration. Medical Physics?32(6), 1647 (2005) CrossRef
  8. Lin, T., Guyader, C.L., Dinov, I., Thompson, P., Toga, A., Vese, L.: A Landmark-Based Image Registration Model using a Nonlinear Elasticity Smoother for Mapping Mouse Atlas to Gene Expression Data. Sciences-New York (2009)
  9. Dumpuri, P., Thompson, R.C., Dawant, B.M., Cao, A., Miga, M.I.: An atlas-based method to compensate for brain shift: Preliminary results. Medical Image Analysis?11(2), 128-45 (2007) CrossRef
  10. Gilles, B., Pai, D.K.: Fast musculoskeletal registration based on shape matching. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds.) MICCAI 2008, Part II. LNCS, vol.?5242, pp. 822-29. Springer, Heidelberg (2008) CrossRef
  11. Marami, B., Sirouspour, S., Capson, D.: Model-based deformable registration of preoperative 3D to intraoperative low-resolution 3D and 2D sequences of MR images. In: Fichtinger, G., Martel, A., Peters, T. (eds.) MICCAI 2011, Part I. LNCS, vol.?6891, pp. 460-67. Springer, Heidelberg (2011) CrossRef
  12. Hu, Y., Ahmed, H.U., Taylor, Z., Allen, C., Emberton, M., Hawkes, D., Barratt, D.: MR to ultrasound registration for image-guided prostate interventions. Medical Image Analysis?16(3), 687-03 (2012) CrossRef
  13. Courtecuisse, H., Peterlik, I., Trivisonne, R., Duriez, C., Cotin, S.: Constraint-based simulation for non-rigid real-time registration. In: Medicine Meets Virtual Reality, MMVR21, California, US (to appear, February 2014)
  14. Rusinkiewicz, S., Levoy, M.: Efficient variants of the ICP algorithm. In: Proc. of 3rd Conf. on 3D Digital Imaging and Modeling, pp. 145-52 (2001)
  15. Vlachos, A., Peters, J., Boyd, C., Mitchell, J.L.: Curved PN triangles. In: Symposium on Interactive 3D Graphics, pp. 159-66 (2001)
  16. Duriez, C., Dubois, F., Kheddar, A., Andriot, C.: Realistic haptic rendering of interacting deformable objects in virtual environments. IEEE Transactions on Visualization and Computer Graphics?12(1), 36-7 (2006) CrossRef
  17. Müller, M., Gross, M.: Interactive virtual materials. In: GI 2004: Proc. of Graphics Interface 2004, School of Computer Science, University of Waterloo, Ontario, Canada, pp. 239-46. Canadian Human-Computer Communications Society (2004)
  
• 作者单位：Igor Peterlik (20) (21) (23)
  Hadrien Courtecuisse (20) (21) (22)
  Christian Duriez (21)
  Stéphane Cotin (20) (21)
  
  20. Institut Hospitalo-Universitaire, Strasbourg, France
  21. SHACRA Team, Inria, France
  23. Institute of Computer Science, Masaryk University, Czech Republic
  22. AVR Team, CNRS, France
  
• ISSN：1611-3349

文摘

In this paper, we present a novel method dealing with the identification of boundary conditions of a deformable organ, a particularly important step for the creation of patient-specific biomechanical models of the anatomy. As an input, the method requires a set of scans acquired in different body positions. Using constraint-based finite element simulation, the method registers the two data sets by solving an optimization problem minimizing the energy of the deformable body while satisfying the constraints located on the surface of the registered organ. Once the equilibrium of the simulation is attained (i.e. the organ registration is computed), the surface forces needed to satisfy the constraints provide a reliable estimation of location, direction and magnitude of boundary conditions applied to the object in the deformed position. The method is evaluated on two abdominal CT scans of a pig acquired in flank and supine positions. We demonstrate that while computing a physically admissible registration of the liver, the resulting constraint forces applied to the surface of the liver strongly correlate with the location of the anatomical boundary conditions (such as contacts with bones and other organs) that are visually identified in the CT images.