Abstract
This article presents an approach for decreasing the computational time for converting a sparse SpatialObject to an Image. The method is applicable for SpatialObjects which occupy less volume than the total output Image (which occurs often, especially when using TubeSpatialObjects to represent vessels). A new filter MaskedSpatialObjectToImageFilter is introduced which dramatically decreases the execution time by creating a mask of relevant pixels. The mask is computed by calling the conventional SpatialObjectToImageFilter at a lower resolution, which is significantly faster for large images. The mask is then up-sampled to control which areas are further processed.