PPDM: Pixel Puzzling Diffusion Model for Speed and Memory Efficient Volumetric Medical Image Translation
Researchers have developed a new method called the Pixel Puzzling Diffusion Model (PPDM) to make volumetric medical image translation more efficient. This approach significantly reduces computational costs and GPU memory usage, by trading spatial resolution for channel dimensionality. PPDM also incorporates a direct bridge diffusion formulation and a puzzle-gradient loss to improve stability and spatial coherence, outperforming existing memory-efficient methods and matching full 3D diffusion models. AI