A Nonrigid Image Registration Framework for Identification of Tissue Mechanical Parameters

Authors:
Petr Jordan;Simona Socrate;Todd E. Zickler;Robert D. Howe
Affiliations:
Harvard School of Engineering and Applied Sciences, , Cambridge, and Harvard-MIT Division of Health Sciences and Technology, , Cambridge,;Department of Mechanical Engineering, MIT, Cambridge,;Harvard School of Engineering and Applied Sciences, , Cambridge,;Harvard School of Engineering and Applied Sciences, , Cambridge, and Harvard-MIT Division of Health Sciences and Technology, , Cambridge,
Venue:
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
Year:
2008

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Abstract

We present a modular framework for mechanically regularized nonrigid image registration of 3D ultrasound and for identification of tissue mechanical parameters. Mechanically regularized deformation fields are computed from sparsely estimated local displacements. We enforce image-based local motion estimates by applying concentrated forces at mesh nodes of a mechanical finite-element model. The concentrated forces are generated by the elongation of regularization springs connected to the mesh nodes as their free ends are displaced according to local motion estimates. The regularization energy corresponding to the potential energy stored in the springs is minimized when the mechanical response of the model matches the observed response of the organ. We demonstrate that this technique is suitable for identification of material parameters of a nonlinear viscoelastic liver model and demonstrate its benefits over traditional indentation methods in terms of improved volumetric agreement between the model response and the experiment.