Metric-guided Image Reconstruction Bounds via Conformal Prediction

arXiv:2404.15274v1 Announce Type: new
Abstract: Recent advancements in machine learning have led to novel imaging systems and algorithms that address ill-posed problems. Assessing their trustworthiness and understanding how to deploy them safely at test time remains an important and open problem. We propose a method that leverages conformal prediction to retrieve upper/lower bounds and statistical inliers/outliers of reconstructions based on the prediction intervals of downstream metrics. We apply our method to sparse-view CT for downstream radiotherapy planning and show 1) …

arxiv cs.cv cs.lg eess.iv image physics.med-ph prediction type via