From: NeurIPS.cc/2021/Workshop/Deep_Inverse/Program_Chairs
title: Paper Decision
decision: Accept (Poster)
comment: This paper introduces an image quality metric for evaluating MRI reconstructions based on the feature distance of an encoder pre-trained in a self-supervised fashion on MRI data. This work is very well-motivated as traditional image quality metrics (SSIM, PSNR) don't necessarily correlate well with the doctor's evaluation. Beyond the initial promising studies presented in the paper, a radiologist's opinion would be crucial to evaluate the utility of this metric in practice, and overall a more extensive evaluation of the image quality metric would be an important next step.