Impact of statistical reconstruction and compressed sensing algorithms on projection data elimination during X-ray CT image reconstruction
Impact of statistical reconstruction and compressed sensing algorithms on projection data elimination during X-ray CT image reconstruction
复制标题
统计重建和压缩感知算法对 X 射线 CT 图像重建过程中投影数据消除的影响
DOI：
10.1007/s11282-017-0308-6
复制
发表时间：
2018
期刊：
影响因子：
2.2
通讯作者：
Hayakawa Yoshihiko
中科院分区：
文献类型：
--
作者：
Sun Bing-Yu;Hayakawa Yoshihiko
目的检查不完整或完全消除投影数据对经过统计重建和/或压缩感知算法的计算机断层扫描 (CT) 图像的影响。方法使用多探测器行 CT 图像。将代数重建技术（ART）和最大似然期望最大化（ML-EM）方法与滤波反投影（FBP）进行比较。研究了通过减小采集角度或细化图像数据，将360°（360个投影）的投影数据减少到180或90个投影时对重建图像的影响。使用压缩感知的全变分（TV）正则化方法应用于 ART 处理的图像。使用均方根误差和信噪比来主观评估图像噪声。结果当投影数据减少二分之一或四分之三时，ART 和 ML-EM 产生的图像质量比 FBP 更好。 ART 和 ML-EM 均可在 180° 旋转范围内分布 90 个投影，从而获得高质量的效果。与 ART 相比，统计重建的计算负荷较高，但 ML-EM 的计算负荷较低。电视正则化使得仅使用 36 个投影成为可能，同时仍然达到可接受的图像质量。结论不完整的投影数据（通过减小收集图像数据的角度或细化投影数据而不减小收集数据的旋转角度来实现）使得可以在通过统计重建算法和/或压缩感知保持图像质量的同时减少辐射剂量。尽管计算负荷较重，但应考虑使用这些方法来减少辐射剂量。
ObjectivesTo examine the effect of incomplete, or total elimination of, projection data on computed tomography (CT) images subjected to statistical reconstruction and/or compressed sensing algorithms.MethodsMultidetector row CT images were used. The algebraic reconstruction technique (ART) and the maximum likelihood-expectation maximization (ML-EM) method were compared with filtered back-projection (FBP). Effects on reconstructed images were studied when the projection data of 360° (360 projections) were decreased to 180 or 90 projections by reducing the collection angle or thinning the image data. The total variation (TV) regularization method using compressed sensing was applied to images processed by the ART. Image noise was subjectively evaluated using the root-mean-square error and signal-to-noise ratio.ResultsWhen projection data were reduced by one-half or three-quarters, ART and ML-EM produced better image quality than FBP. Both ART and ML-EM resulted in high quality at a spread of 90 projections over 180° rotation. Computational loading was high for statistical reconstruction, but not for ML-EM, compared with the ART. TV regularization made it possible to use only 36 projections while still achieving acceptable image quality.ConclusionsIncomplete projection data—accomplished by reducing the angle to collect image data or thinning the projection data without reducing the angle of rotation over which it is collected—made it possible to reduce the radiation dose while retaining image quality with statistical reconstruction algorithms and/or compressed sensing. Despite heavier computational calculation loading, these methods should be considered for reducing radiation doses.