A combined registration and finite element analysis method for fast estimation of intraoperative brain shift; phantom and animal model study.

Background: Finite element models for estimation of intraoperative brain shift suffer from huge computational cost. In these models, image registration and finite element analysis are two time-consuming processes.

Methods: The proposed method is an improved version of our previously developed Finite Element Drift (FED) registration algorithm.

Estimation of intraoperative brain shift by combination of stereovision and doppler ultrasound: phantom and animal model study.

Purpose: Combination of various intraoperative imaging modalities potentially can reduce error of brain shift estimation during neurosurgical operations. In the present work, a new combination of surface imaging and Doppler US images is proposed to calculate the displacements of cortical surface and deformation of internal vessels in order to estimate the targeted brain shift using a Finite Element Model (FEM). Registration error in each step and the overall performance of the method are evaluated.