Adapting image editing foundation models via LoRA with multi-reference conditioning achieves state-of-the-art CT metal artifact reduction using two orders of magnitude less paired training data than prior methods.
Conditional generative adversarial networks for metal artifact reduction in CT images of the ear.Med
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Leveraging Image Editing Foundation Models for Data-Efficient CT Metal Artifact Reduction
Adapting image editing foundation models via LoRA with multi-reference conditioning achieves state-of-the-art CT metal artifact reduction using two orders of magnitude less paired training data than prior methods.