Exploring out-of-distribution detection for sparse-view computed tomography with diffusion models
Abstract Recent works demonstrate the effectiveness of diffusion models as unsupervised solvers for inverse imaging problems. Sparse-view computed tomography (CT) has greatly benefited from these advancements, achieving improved generalization without reliance on measurement parameters. However, this comes at the cost...
Ezgi Demircan-Tureyen, Felix F. Lucka, Tristan van Leeuwen
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