Abdominal ultrasound simulation drops the patient CT at inference: semantic labels drive physics-based images, and editing the map controls deformation and lesions
Abdominal ultrasound simulation has largely relied on patient CT for ray-casting, which limits control over deformation and pathology. A two-stage pipeline first synthesizes a simplified physics-based ultrasound image from anatomical semantic labels, then refines it into a realistic scan with anatomy-guided unpaired translation, so no patient-specific CT volume is needed at inference. In stage one the semantic diffusion model beat Pix2Pix on morphological metrics while Pix2Pix scored better on perceptual ones; training still requires CT-derived segmentations and ray-casting simulations.