2023
Stay In The Middle: A Semi-Supervised Model for CT Metal Artifact Reduction
ICASSP 2023accepted
Metal artifacts degrade CT image’s quality. Recently, some deep learning-based metal artifact reduction (MAR) methods have been developed. Supervised MAR methods don’t perform well in clinical due to the domain gap between simulated and clinical data. Although this problem can be avoided in an unsup…