Robust and Scalable Interactive Freeform Modeling of High Definition Medical Images
Abstract
Whole-body anatomically correct high-resolution 3D medical
images are instrumental for physical simulations. Unfortunately, only
a limited number of acquired datasets are available and the scope of
possible applications is limited by the patient's posture. In this paper,
we propose an extension of the interactive cage-based deformation
pipeline VoxMorph [1], for labeled voxel grids allowing to eciently explore
the space of plausible poses while preserving the tissues' internal
structure. We propose 3 main contributions to overcome the limitations
of this pipeline: (i) we improve the robustness by proposing a deformation
diusion scheme, (ii) we improve the accuracy by proposing a new
error-metric for the renement process of the motion adaptive structure,
(iii) we improve the scalability by proposing an out-of-core implementation.
Our method is easy to use for novice users, robust and scales up
to 3D images that do not t in memory, while oering limited distortion
and mass loss. We evaluate our approach on postured whole-body segmented
images and present an electro-magnetic wave exposure study for
human-waves interaction simulations.