In this paper, we evaluate the target position estimation accuracy of a novel soft tissue navigation system with a
custom-designed respiratory liver motion simulator. The system uses a real-time deformation model to estimate
the position of the target (e.g. a tumor) during a minimally invasive intervention from the location of a set of
optically tracked needle-shaped navigation aids which are placed in the vicinity of the target.
A respiratory liver motion simulator was developed to evaluate the performance of the system in-vitro. It
allows the mounting of an explanted liver which can be moved along the longitudinal axis of a corpus model to
simulate breathing motion. In order to assess the accuracy of our system we utilized an optically trackable tool
as target and estimated its position continuously from the current position of the navigation aids. Four different
transformation types were compared as base for the real-time deformation model: Rigid transformations, thinplate
splines, volume splines, and elastic body splines. The respective root-mean-square target position estimation
errors are 2.15 mm, 1.60 mm, 1.88 mm, and 1.92 mm averaged over a set of experiments obtained from a total
of six navigation aid configurations in two pig livers. The error is reduced by 76.3%, 82.4%, 79.3%, and 78.8%,
respectively, compared to the case when no deformation model is applied, i.e., a constant organ position is
assumed throughout the breathing cycle.