A nonrigid image registration framework for identification of tissue mechanical parameters.
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.
Jordan
Petr
P
Harvard School of Engineering and Applied Sciences, Cambridge, MA, USA.
Socrate
Simona
S
Zickler
Todd E
TE
Howe
Robert D
RD
D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D004548:Elasticity; D054459:Elasticity Imaging Techniques / Q000379:methods*; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D066298:In Vitro Techniques; D008099:Liver / Q000000981:diagnostic imaging* / Q000502:physiology*; D008954:Models, Biological; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013314:Stress, Mechanical; D013382:Subtraction Technique; D013552:Swine