Echo-DM: Ultrasound Marker Removal via Conditional Latent Diffusion and Region-Aware Fusion
Researchers have developed Echo-DM, a novel framework for removing artificial markers from clinical ultrasound images. This method utilizes a conditional latent diffusion model combined with region-aware fusion to restore images without relying on masks, preserving anatomical details. Experiments on the Echo-PAIR dataset show Echo-DM outperforms existing methods in marker removal and anatomical fidelity, offering efficient deployment options. AI
IMPACT This new method could improve the accuracy of automated analysis in clinical ultrasound imaging by removing distracting artificial markers.