Bayesian estimation of non-rigid mechanical parameters using temporal sequences of deformation samples

Abstract

Material property has great importance in medical robotics. The mechanical properties of the human soft tissue, are important to characterize the tissue deformation of each patient. The (recovered) elasticity parameters can assist surgeons to perform better pre-op surgical planning and enable medical robots to carry out personalized surgical procedures. In this paper, we present a novel algorithm on mechanical-property estimation from a temporal sequence of deformation samples. It does not require an external force-application measurement device or landmark-based displacement tracking. We test our approach on the reconstruction the Young's modulus of a human heart and further validate the results derived from videos using known parameters of tennis and foam balls.