CT-DegradBench is a new benchmark dataset for CT degradation detection and severity estimation, with the SeSpeCT framework using semantic priors from vision-language models and frequency features to predict artifact types and levels without fine-tuning.
Tmaa-net: Tensor-domain multi-planal anti-aliasing network for sparse-view ct image reconstruc- tion.Physics in Medicine & Biology, 69(22):225012
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CT-DegradBench: A Physics-Informed Benchmark for CT Degradation Detection and Severity Estimation
CT-DegradBench is a new benchmark dataset for CT degradation detection and severity estimation, with the SeSpeCT framework using semantic priors from vision-language models and frequency features to predict artifact types and levels without fine-tuning.