AI RESEARCH
CT-DegradBench: A Physics-Informed Benchmark for CT Degradation Detection and Severity Estimation
arXiv CS.CV
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ArXi:2605.16431v1 Announce Type: new Computed tomography (CT) images are frequently degraded by acquisition artifacts, including noise, blur, streaking, aliasing, and metal artifacts. Yet CT enhancement is still largely evaluated using image quality metrics with limited perceptual and clinical validity, while existing datasets remain focused on isolated restoration tasks, hindering unified benchmarking across diverse degradation types. We present CT-DegradBench, a dataset and benchmark for CT degradation detection and severity estimation under controlled single- and mixed-artifact settings.