Prior-Guided Metal Artifact Reduction for Iterative X-Ray Computed Tomography

被引:21
|
作者
Chang, Zhiqian [1 ]
Ye, Dong Hye [2 ]
Srivastava, Somesh [3 ]
Thibault, Jean-Baptiste [3 ]
Sauer, Ken [4 ]
Bouman, Charles [2 ]
机构
[1] Intel Corp, Hillsboro, OR 97124 USA
[2] Purdue Univ, Dept Elect & Comp Engn, W Lafayette, IN 47907 USA
[3] GE Healthcare, Appl Sci Lab, Waukesha, WI 53188 USA
[4] Univ Notre Dame, Dept Elect Engn, Notre Dame, IN 46556 USA
关键词
Statistical reconstruction; iterative reconstruction; metal artifact reduction; beam hardening correction; computed tomography; STATISTICAL IMAGE-RECONSTRUCTION; SPATIAL-RESOLUTION; PROJECTION; MODEL; ALGORITHM; HARDWARE; BONE; MAP;
D O I
10.1109/TMI.2018.2886701
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
High-attenuation materials pose significant challenges to computed tomographic imaging. Formed of high mass-density and high atomic number elements, they cause more severe beam hardening and scattering artifacts than dowater-like materials. Pre-corrected line-integral density measurements are no longer linearly proportional to the path lengths, leading to reconstructed image suffering from streaking artifacts extending from metal, often along highest-density directions. In this paper, a novel prior-based iterative approach is proposed to reduce metal artifacts. It combines the superiority of statistical methods with the benefits of sinogram completion methods to estimate and correct metal-induced biases. Preliminary results show minimized residual artifacts and significantly improved image quality.
引用
收藏
页码:1532 / 1542
页数:11
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