  Current virtual reality (VR) training simulators of liver punctures often
rely on static 3D patient data and use an unrealistic (sinusoidal) periodic
animation of the respiratory movement. Existing methods for the animation of
breathing motion support simple mathematical or patient-specific, estimated
breathing models. However with personalized breathing models for each new
patient, a heavily dose relevant or expensive 4D data acquisition is mandatory
for keyframe-based motion modeling. Given the reference 4D data, first a model
building stage using linear regression motion field modeling takes place. Then
the methodology shown here allows the transfer of existing reference
respiratory motion models of a 4D reference patient to a new static 3D patient.
This goal is achieved by using non-linear inter-patient registration to warp
one personalized 4D motion field model to new 3D patient data. This cost- and
dose-saving new method is shown here visually in a qualitative proof-of-concept
study.
