Sun Bing-Yu, Hayakawa Yoshihiko
Course of Medical Engineering, Graduate School of Engineering, Kitami Institute of Technology, 165 Koencho, Kitami, Hokkaido, 090-8507, Japan.
Department of Engineering on Intelligent Machines and Biomechanics, School of Regional Innovation and Social Design Engineering, Faculty of Engineering, Kitami Institute of Technology, 165 Koencho, Kitami, Hokkaido, 090-8507, Japan.
Oral Radiol. 2018 Sep;34(3):237-244. doi: 10.1007/s11282-017-0308-6. Epub 2017 Dec 6.
To 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.
Multidetector 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.
When 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.
Incomplete 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.
研究投影数据不完全消除或完全消除对采用统计重建和/或压缩感知算法的计算机断层扫描（CT）图像的影响。
使用多排探测器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。通过减小采集角度或稀疏图像数据，将360°（360个投影）的投影数据减少到180个或90个投影时，研究对重建图像的影响。将使用压缩感知的总变差（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主观评估图像噪声。
当投影数据减少二分之一或四分之三时，ART和ML-EM产生的图像质量优于FBP。在180°旋转范围内90个投影的分布情况下，ART和ML-EM均产生高质量图像。与ART相比，统计重建的计算量很大，但ML-EM的计算量不大。TV正则化使得仅使用36个投影仍能获得可接受的图像质量。
通过减小采集图像数据的角度或稀疏投影数据（而不减小采集投影数据的旋转角度）来实现不完全投影数据，这使得在使用统计重建算法和/或压缩感知时，在保持图像质量的同时降低辐射剂量成为可能。尽管计算量较大，但为了降低辐射剂量，仍应考虑这些方法。
