Simultaneous Estimation of Elasticity for
Multiple Deformable Bodies

Shan Yang, Ming C. Lin

Material property has great importance in deformable body simulation and medical robotics. The elasticity parameters, such as Young's modulus of the deformable bodies, are important to make realistic animations. Further, in medical applications, the (recovered) elasticity parameters can assist surgeons to perform better pre-op surgical planning and enable medical robots to carry out personalized surgical procedures. Previous elasticity parameters estimation methods are limited to recover one elasticity parameter of one deformable body at a time. In this paper, we propose a novel elasticity parameter estimation algorithm that can recover the elasticity parameters of multiple deformable bodies or multiple regions of one deformable body simultaneously from (at least two sets of) images. We validate our algorithm with both synthetic test cases and real patient computed tomography images.