Compressive sampling photoacoustic tomography based on edge expander codes and TV regularization
A new photoacoustic (PA) signal sampling and image reconstruction method, called compressive sampling PA tomography (CSPAT), is recently proposed to make low sampling rate and high-resolution PA tomography possible. A key problem within the CSPAT framework is the design of optic masks. We propose to use edge expander codes-based masks instead of the conventional random distribution masks, and efficient total variation (TV) regularization-based model to formulate the associated problem. The edge expander codes-based masks, corresponding to non-uniform sampling schemes, are validated by both theoretical analysis and results from computer simulations. The proposed method is expected to enhance the capability of CSPAT for reducing the number of measurements and fast data acquisition.
Mingjian Sun：Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, China
Qiang Wang：Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, China
Naizhang Feng：Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, China
Yi Shen：Department of Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, China
备注：This work was supported by the National Natural Science Foundation of China (Nos. 61174016, 61201307, and 61371045) and the Fundamental Research Funds for the Central Universities (No. HIT. NSRIF. 2013132).
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Zhenghua Wu, Mingjian Sun, Qiang Wang, Naizhang Feng, Yi Shen, "Compressive sampling photoacoustic tomography based on edge expander codes and TV regularization," Chinese Optics Letters 12(10), 101102 (2014)
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