Research Papers: Imaging

Efficient discrete cosine transform model–based algorithm for photoacoustic image reconstruction

[+] Author Affiliations
Yan Zhang, Yuanyuan Wang, Chen Zhang

Fudan University, Department of Electronic Engineering, Shanghai 200437, China

J. Biomed. Opt. 18(6), 066008 (Jun 03, 2013). doi:10.1117/1.JBO.18.6.066008
History: Received January 19, 2013; Revised April 27, 2013; Accepted May 10, 2013
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Abstract.  The model-based algorithm is an effective reconstruction method for photoacoustic imaging (PAI). Compared with the analytical reconstruction algorithms, the model-based algorithm is able to provide a more accurate and high-resolution reconstructed image. However, the relatively heavy computational complexity and huge memory storage requirement often impose restrictions on its applications. We incorporate the discrete cosine transform (DCT) in PAI reconstruction and establish a new photoacoustic model. With this new model, an efficient algorithm is proposed for PAI reconstruction. Relatively significant DCT coefficients of the measured signals are used to reconstruct the image. As a result, the calculation can be saved. The theoretical computation complexity of the proposed algorithm is figured out and it is proved that the proposed method is efficient in calculation. The proposed algorithm is also verified through the numerical simulations and in vitro experiments. Compared with former developed model-based methods, the proposed algorithm is able to provide an equivalent reconstruction with the cost of much less time. From the theoretical analysis and the experiment results, it would be concluded that the model-based PAI reconstruction can be accelerated by using the proposed algorithm, so that the practical applicability of PAI may be enhanced.

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© 2013 Society of Photo-Optical Instrumentation Engineers

Citation

Yan Zhang ; Yuanyuan Wang and Chen Zhang
"Efficient discrete cosine transform model–based algorithm for photoacoustic image reconstruction", J. Biomed. Opt. 18(6), 066008 (Jun 03, 2013). ; http://dx.doi.org/10.1117/1.JBO.18.6.066008


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