Abstract
The estimation of soft tissue deformation from 3D image sequences is an important problem in a number of fields such as diagnosis of heart disease and image guided surgery. In this paper we describe a methodology for using biomechanical material models, within a Bayesian framework which allows for proper modeling of image noise, in order to estimate these deformations. The resulting partial differential equations are discretized and solved using the finite element method. We demonstrate the application of this method to estimating strains from sequences of in-vivo left ventricular MR images, where we incorporate information about the fibrous structure of the ventricle. The deformation estimates obtained exhibit similar patterns with measurements obtained from more invasive techniques, used as a gold standard.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Bathe. K. Finite Element Procedures in Engineering Analysis. Prentice-Hall, New Jersey, 1982.
Christiansen G. E., Rabbitt R. D., and Miller M. I. 3D Brain mapping using deformable neuroanatomy. Physics in Medicine and Biology, 39:609–618, 1994.
Dione D. P., Shi P., Smith W, De Man P., Soares J., Duncan J.S., and Sinusas A.J. Three-dimensional regional left ventricular deformation from digital sonomicrometry. In 19th Ann. Int. Conf. of the IEEE Engineering in Medicine and Biology Society, pages 848–851, Chigago, IL, March 1997.
Edwards P. J., Hill D.L.G., Little J.A., and Hawkes D.J. Deformation for image guided interventions using a three component tissue model. In Information Processing in Medical Imaging, pages 218–231, Vermont, USA, June 1997.
Guccione J. M. and McCulloch A. D.. Finite element modeling of ventricular mechanics. In Hunter P.J., McCulloch A. D., and Nielsen P., editors, Theory of Heart, pages 122–144. Springer-Verlag, Berlin, 1991.
Mendis K.K., Stalnaker R.L., and Advani S.H. A constitutive relationship for large deformation finite element modeling of brain tissue. Journal of Biomechanical Engineering, 117(3):279–85, 1995.
Papademetris X., Rambo J., Dione D.P, Sinusas A.J., and Duncan J.S. Visually interactive cine-3D segmentation of cardiac mr images. Suppl. Journ. of the American College of Cardiology Volume 31, #2 (Supplement A), February 1998.
Papademetris X. and Shi P. and Dione D.P. and Sinusas A.J. and Constable R.T. and Duncan J.S. Recovery of Soft Tissue Object Deformation from 3D Image Sequences using Biomechanical Models Technical Report 1999-01, Image Processing and Analysis Group, Dept. of Diagnostic Radiology, Yale University, March 1998.
Park J., Metaxas D., and Axel L.. Volumetric deformable models with parameter functions: a new approach to the 3D motion analysis of the LV from MRI-SPAMM. In Fifth International Conference on Computer Vision, pages 700–705, 1995.
Prince J. L. and McVeigh E. R. Motion estimation from tagged mr image sequences. IEEE Transactions on Medical Imaging, 11:238–249, June 1992.
Shi P., Sinusas A.J., Constable R.T., Ritman E., and Duncan J.S. Point-tracked quantitative analysis of left ventricular motion from 3D image sequences. IEEE Transactions on Medical Imaging, in-press.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1999 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Papademetris, X., Shi, P., Dione, D.P., Sinusas, A.J., Todd Constable, R., Duncan, J.S. (1999). Recovery of Soft Tissue Object Deformation from 3D Image Sequences Using Biomechanical Models. In: Kuba, A., Šáamal, M., Todd-Pokropek, A. (eds) Information Processing in Medical Imaging. IPMI 1999. Lecture Notes in Computer Science, vol 1613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48714-X_28
Download citation
DOI: https://doi.org/10.1007/3-540-48714-X_28
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66167-2
Online ISBN: 978-3-540-48714-2
eBook Packages: Springer Book Archive