Improving Medical Image Generative Models with Fréchet Distance Loss

Jul 16, 2026

Researchers propose a new finetuning method called Fréchet Distance loss (FD-loss) to improve diffusion generative models for medical images. By aligning feature statistics between real and generated images, FD-loss enhances the fidelity of synthetic tumor images, leading to over 5% improvement in downstream segmentation performance on liver and brain cancer datasets. The approach reduces segmentation hallucinations and produces more realistic tumor morphologies.

Why it matters: This work offers a practical advance for medical image synthesis by addressing the tendency of diffusion models to oversmooth irregular tumor boundaries, thereby improving the clinical utility of synthetic data for segmentation tasks.

Full story at: arXiv Computer Vision ↗