Transformation-driven generation of comparable projection images from multimodal anatomical scenes
Researchers have developed a new framework for generating synthetic projection images from complex anatomical scenes, particularly focusing on scenarios involving spatial transformations like mandibular motion. This method differs from traditional Digitally Reconstructed Radiograph (DRR) approaches by treating projection imaging as an observation process within an explicitly represented anatomical scene. The framework allows for independent transformations of volumetric and surface-based objects, enabling controlled exploration of anatomical-projection relationships and transformation-aware imaging workflows. AI