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Found 4 papers, 2 papers with code
Feature Extraction for Generative Medical Imaging Evaluation: New Evidence Against an Evolving Trend
A recent trend is to adapt FID to medical imaging through feature extractors trained on medical images.
Ranked #1 on
Medical Image Generation
on SLIVER07
Dimensionality Reduction for Improving Out-of-Distribution Detection in Medical Image Segmentation
Clinically deployed segmentation models are known to fail on data outside of their training distribution.
StyleGAN2-based Out-of-Distribution Detection for Medical Imaging
Our OOD test data consisted of CT images of the brain, head and neck, lung, cervix, and abnormal livers.
Evaluating the Performance of StyleGAN2-ADA on Medical Images
Our computational ablation study revealed that transfer learning and data augmentation stabilize training and improve the perceptual quality of the generated images.
Ranked #1 on
Medical Image Generation
on ACDC
