Distilling Photon-Counting CT into Routine Chest CT through Clinically Validated Degradation Modeling
Photon-counting CT (PCCT) provides superior image quality with higher spatial resolution and lower noise compared to conventional energy-integrating CT (EICT), but its limited clinical availability restricts large-scale research and clinical deployment. To bridge this gap, we propose SUMI, a simulated degradation-to-enhancement method that learns to reverse realistic acquisition artifacts in low-quality EICT by leveraging high-quality PCCT as reference. Our central insight is to explicitly model realistic acquisition degradations, transforming PCCT into clinically plausible lower-quality counterparts and learning to invert this process. The simulated degradations were validated for clinic...
| Authors | Junqi Liu, Xinze Zhou, Wenxuan Li et al. |
|---|---|
| Primary category | cs.CV |
| Published | 8 April 2026 |
| Last updated at source | 8 April 2026 |
Models and datasets referencing this paper
- MitakaKuma/LUNA16Dataset
- MitakaKuma/SUMI-OpenCTDataset
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