Cerebral perfusion computed tomography deconvolution via structure tensor total variation regularization

被引:26
|
作者
Zeng, Dong [1 ,2 ]
Zhang, Xinyu [1 ,2 ]
Bian, Zhaoying [1 ,2 ]
Huang, Jing [1 ,2 ]
Zhang, Hua [1 ,2 ]
Lu, Lijun [1 ,2 ]
Lyu, Wenbing [1 ,2 ]
Zhang, Jing [3 ]
Feng, Qianjin [1 ,2 ]
Chen, Wufan [1 ,2 ]
Ma, Jianhua [1 ,2 ]
机构
[1] Southern Med Univ, Dept Biomed Engn, Guangzhou 510515, Guangdong, Peoples R China
[2] Southern Med Univ, Guangdong Prov Key Lab Med Image Proc, Guangzhou 510515, Guangdong, Peoples R China
[3] Tianjin Med Univ, Gen Hosp, Dept Radiol, Tianjin 300052, Peoples R China
基金
中国国家自然科学基金;
关键词
cerebral perfusion computed tomography; low-mAs; deconvolution; structure tensor total variation; regularization; CLINICAL-APPLICATIONS; IMAGE-RECONSTRUCTION; NOISE-REDUCTION; CT; QUALITY; PARAMETERS; ALGORITHM; VOLUME; SCAN; FLOW;
D O I
10.1118/1.4944866
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: Cerebral perfusion computed tomography (PCT) imaging as an accurate and fast acute ischemic stroke examination has been widely used in clinic. Meanwhile, a major drawback of PCT imaging is the high radiation dose due to its dynamic scan protocol. The purpose of this work is to develop a robust perfusion deconvolution approach via structure tensor total variation (STV) regularization (PD-STV) for estimating an accurate residue function in PCT imaging with the low-milliampere-seconds (low-mAs) data acquisition. Methods: Besides modeling the spatio-temporal structure information of PCT data, the STV regularization of the present PD-STV approach can utilize the higher order derivatives of the residue function to enhance denoising performance. To minimize the objective function, the authors propose an effective iterative algorithm with a shrinkage/thresholding scheme. A simulation study on a digital brain perfusion phantom and a clinical study on an old infarction patient were conducted to validate and evaluate the performance of the present PD-STV approach. Results: In the digital phantom study, visual inspection and quantitative metrics (i.e., the normalized mean square error, the peak signal-to-noise ratio, and the universal quality index) assessments demonstrated that the PD-STV approach outperformed other existing approaches in terms of the performance of noise-induced artifacts reduction and accurate perfusion hemodynamic maps (PHM) estimation. In the patient data study, the present PD-STV approach could yield accurate PHM estimation with several noticeable gains over other existing approaches in terms of visual inspection and correlation analysis. Conclusions: This study demonstrated the feasibility and efficacy of the present PD-STV approach in utilizing STV regularization to improve the accuracy of residue function estimation of cerebral PCT imaging in the case of low-mAs. (C) 2016 American Association of Physicists in Medicine.
引用
收藏
页码:2091 / 2107
页数:17
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