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.