X射线断层成像中带有不确定平坦场的凸重建模型
A Convex Reconstruction Model for X-ray Tomographic Imaging with Uncertain Flat-fields
AI总结：
本文提出一种新的凸模型，用于处理X射线断层成像中平坦场的不确定性，以提高重建质量，尤其在动态CT等对时间和剂量敏感的应用中减少环状伪影。
摘要：
经典X射线计算机断层成像方法基于假设X射线源强度已知，但实际上该强度是测量得到的，因此存在不确定性。在正常工作条件下，当曝光时间足够高时，这种不确定性通常对重建质量影响很小。然而，在时间或剂量受限的应用中，如动态CT，这种不确定性可能导致严重的系统性伪影，即环状伪影。通过仔细建模测量过程并考虑不确定性，我们推导出一个新的凸模型，即使在低质量测量情况下也能实现改进的重建。我们基于模拟和真实数据集展示了该方法的有效性。
英文摘要：
Classical methods for X-ray computed tomography are based on the assumption that the X-ray source intensity is known, but in practice, the intensity is measured and hence uncertain. Under normal operating conditions, when the exposure time is sufficiently high, this kind of uncertainty typically has a negligible effect on the reconstruction quality. However, in time- or dose-limited applications such as dynamic CT, this uncertainty may cause severe and systematic artifacts known as ring artifacts. By carefully modeling the measurement process and by taking uncertainties into account, we derive a new convex model that leads to improved reconstructions despite poor quality measurements. We demonstrate the effectiveness of the methodology based on simulated and real data sets.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
