| High total variation-based method for sparse-view photoacoustic reconstruction |
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| 作者姓名： | Chen Zhang Yuanyuan Wang |
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| 作者单位： | Chen Zhang:Department of Electronic Engineering, Fudan University, Shanghai 200433, China
Yuanyuan Wang:Department of Electronic Engineering, Fudan University, Shanghai 200433, ChinaKey Laboratory of Medical Imaging Computing and Computer Assisted Intervention, Shanghai 200433, China
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| 基金项目： | supported by the National Natural Science Foundation of China(Nos.61271071 and 11228411);the National Key Technology R&;D Program of China(No.2012BAI13B02);the Specialized Research Fund for the Doctoral Program of Higher Education of China(No.20110071110017) |
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| 摘 要： | We propose a novel method by combining the total variation（TV） with the high-degree TV（HDTV） to improve the reconstruction quality of sparse-view sampling photoacoustic imaging（PAI）. A weighing function is adaptively updated in an iterative way to combine the solutions of the TV and HDTV minimizations. The fast iterative shrinkage/thresholding algorithm is implemented to solve both the TV and the HDTV minimizations with better convergence rate. Numerical results demonstrate the superiority and efficiency of the proposed method on sparse-view PAI. In vitro experiments also illustrate that the method can be used in practical sparse-view PAI.
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| 关 键 词： | 光声成像 稀疏 基础 HDTV 快速迭代 PAI 重建质量 收敛速度 |
| 收稿时间： | 2014/6/25 |
High total variation-based method for sparse-view photoacoustic reconstruction |
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| Chen Zhang,Yuanyuan Wang.High total variation-based method for sparse-view photoacoustic reconstruction[J].中国光学快报(英文版),2014,12(11):111703-85. |
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| Abstract: | We propose a novel method by combining the total variation(TV) with the high-degree TV(HDTV) to improve the reconstruction quality of sparse-view sampling photoacoustic imaging(PAI). A weighing function is adaptively updated in an iterative way to combine the solutions of the TV and HDTV minimizations. The fast iterative shrinkage/thresholding algorithm is implemented to solve both the TV and the HDTV minimizations with better convergence rate. Numerical results demonstrate the superiority and efficiency of the proposed method on sparse-view PAI. In vitro experiments also illustrate that the method can be used in practical sparse-view PAI. |
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| Keywords: | 110 5120 100 3010 170 3880 170 5120 |
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