Rethinking Perceptual Metrics for Medical Image Translation

arXiv:2404.07318v1 Announce Type: cross
Abstract: Modern medical image translation methods use generative models for tasks such as the conversion of CT images to MRI. Evaluating these methods typically relies on some chosen downstream task in the target domain, such as segmentation. On the other hand, task-agnostic metrics are attractive, such as the network feature-based perceptual metrics (e.g., FID) that are common to image translation in general computer vision. In this paper, we investigate evaluation metrics for medical image translation on …

abstract arxiv conversion cs.cv cs.lg domain eess.iv generative generative models image images medical metrics modern mri network segmentation tasks translation type