Super-resolution dual-energy CT reconstruction based on a discrete focal spot model

The aim of this study was to improve spatial resolution and material decomposition ac curacy in dual-energy computed tomography (DECT) by addressing image degradation caused by focal spot blur ring.

We proposed a weighted super-resolution DECT reconstruction framework based on a discrete focal spot model. A nonlinear imaging model that incorporates focal spot geometry and dual-energy acquisition was constructed by using experimentally measured spot characteristics. On this basis, a high-precision iterative reconstruction method was developed. A novel residual dependent adaptive weighting strategy was introduced to guide the update of material basis images during iterations, thus enabling the method to focus on poorly reconstructed regions and enhancing robustness.

Experiments were conducted on both simulated and real DECT datasets with various focal spot sizes and noise levels. The proposed method consistently outperformed conventional re construction methods and achieved superior spatial resolution and improved material decomposition accuracy. Ablation studies further validated the contribution of the adaptive weighting strategy to the reconstruction quality.

By modeling focal spot effects explicitly and incorporating an adaptive weighting mechanism, the proposed approach effectively mitigates resolution loss and instability in DECT reconstruction.

This work introduces a generalizable and practical solution for enhancing image quality in DECT, with potential effects on high-precision biomedical imaging and clinical diagnostics.