Dynamic Mode Decomposition for soft tissue deformation modelling
Jialu Song, Hujin Xie, Yongmin Zhong, Chengfan Gu, Kup‐Sze Choi
Abstract
This paper studies a new approach to dynamic modelling of soft tissue nonlinear deformation behavior based on dynamic model decomposition. This approach derives the deformation relationship between two continuous time points from correlated system snapshots. Subsequently, it constructs a reduced-order system by extracting most relevant information via thin-singular value decomposition to capture dynamic characteristics of the full-order deformation system. Unlike the existing methods which mainly rely on the establishment of complex constitutive equations for governing soft tissue deformation, the proposed method conducts tissue deformation directly from measured samples without involving constitutive governing equations. Simulation results show that the proposed method not only achieves real-time performance, but also sustains similar accuracy as the nonlinear finite element method.