A parallel resampling method for interactive deformation of volumetric models

In this work, we propose a method to interactively deform high-resolution volumetric datasets, such as those obtained through medical imaging. Interactive deformation enables the visualization of these datasets in full detail using state-of-the-art volume rendering techniques as they are dynamically modified. Our approach relies on resampling the original dataset to a target regular grid, following a 3D rasterization technique. We employ an implicit auxiliary mesh to execute resampling, which allows us to decouple mapping of the deformation field to the volume from actual resampling. In this way, our method is practically independent of the deformation method of choice, as well as of the resolution of the deformation meshes. We show how our method lends itself nicely to an efficient, massively parallel implementation on GPUs, and we demonstrate its application on several high-resolution datasets and deformation models. Graphical abstractDisplay Omitted HighlightsAn interactive resampling algorithm of deformable volumetric models is presented.Algorithm and performance independent of the deformation method and its resolution.Enables interactive volume rendering of deformable high-resolution datasets.Topology changes can be introduced interactively.Performance advantages are analyzed using three deformation methods.