3 papers
cs.CV2025
Quantifying the uncertainty of model-based synthetic image quality metrics
Ciaran Bench, Spencer A. Thomas
The quality of synthetically generated images (e.g. those produced by diffusion models) are often evaluated using information about image contents encoded by pretrained auxiliary m…
eess.IV2025
Style transfer as data augmentation: evaluating unpaired image-to-image translation models in mammography
Emir Ahmed, Spencer A. Thomas, Ciaran Bench
Several studies indicate that deep learning models can learn to detect breast cancer from mammograms (X-ray images of the breasts). However, challenges with overfitting and poor ge…
eess.IV2025
Trustworthy image-to-image translation: evaluating uncertainty calibration in unpaired training scenarios
Ciaran Bench, Emir Ahmed, Spencer A. Thomas
Mammographic screening is an effective method for detecting breast cancer, facilitating early diagnosis. However, the current need to manually inspect images places a heavy burden…