Prior-based artifact correction (PBAC) in computed tomography

被引:31
|
作者
Heusser, Thorsten [1 ]
Brehm, Marcus [1 ]
Ritschl, Ludwig [2 ]
Sawall, Stefan [1 ,3 ]
Kachelriess, Marc [1 ,3 ]
机构
[1] German Canc Res Ctr, D-69120 Heidelberg, Germany
[2] Ziehm Imaging GmbH, D-90451 Nurnberg, Germany
[3] Univ Erlangen Nurnberg, Inst Med Phys, D-91052 Erlangen, Germany
关键词
metal artifact reduction; truncation artifact reduction; limited angle artifact reduction; prior knowledge; sinogram inpainting; CONE-BEAM CT; FIELD-OF-VIEW; PRINCIPAL COMPONENT ANALYSIS; RADIATION-THERAPY; IMAGE-RECONSTRUCTION; SHADING CORRECTION; PROJECTION DATA; PLANNING CT; REDUCTION; ALGORITHM;
D O I
10.1118/1.4851536
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: Image quality in computed tomography (CT) often suffers from artifacts which may reduce the diagnostic value of the image. In many cases, these artifacts result from missing or corrupt regions in the projection data, e.g., in the case of metal, truncation, and limited angle artifacts. The authors propose a generalized correction method for different kinds of artifacts resulting from missing or corrupt data by making use of available prior knowledge to perform data completion. Methods: The proposed prior-based artifact correction (PBAC) method requires prior knowledge in form of a planning CT of the same patient or in form of a CT scan of a different patient showing the same body region. In both cases, the prior image is registered to the patient image using a deformable transformation. The registered prior is forward projected and data completion of the patient projections is performed using smooth sinogram inpainting. The obtained projection data are used to reconstruct the corrected image. Results: The authors investigate metal and truncation artifacts in patient data sets acquired with a clinical CT and limited angle artifacts in an anthropomorphic head phantom data set acquired with a gantry-based flat detector CT device. In all cases, the corrected images obtained by PBAC are nearly artifact-free. Compared to conventional correction methods, PBAC achieves better artifact suppression while preserving the patient-specific anatomy at the same time. Further, the authors show that prominent anatomical details in the prior image seem to have only minor impact on the correction result. Conclusions: The results show that PBAC has the potential to effectively correct for metal, truncation, and limited angle artifacts if adequate prior data are available. Since the proposed method makes use of a generalized algorithm, PBAC may also be applicable to other artifacts resulting from missing or corrupt data. (C) 2014 American Association of Physicists in Medicine.
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页数:16
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