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Chinese Optics Letters

Chinese Optics Letters


  • Vol. 9, Iss. 6 — Jun. 10, 2011
  • pp: 061002–

Photoacoustic image reconstruction based on Bayesian compressive sensing algorithm

Mingjian Sun, Naizhang Feng, Yi Shen, Jiangang Li, Liyong Ma, and Zhenghua Wu  »View Author Affiliations

Chinese Optics Letters, Vol. 9, Issue 6, pp. 061002- (2011)

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The photoacoustic tomography (PAT) method, based on compressive sensing (CS) theory, requires that, for the CS reconstruction, the desired image should have a sparse representation in a known transform domain. However, the sparsity of photoacoustic signals is destroyed because noises always exist. Therefore, the original sparse signal cannot be effectively recovered using the general reconstruction algorithm. In this study, Bayesian compressive sensing (BCS) is employed to obtain highly sparse representations of photoacoustic images based on a set of noisy CS measurements. Results of simulation demonstrate that the BCS-reconstructed image can achieve superior performance than other state-of-the-art CS-reconstruction algorithms.

© 2011 Chinese Optics Letters

OCIS Codes
(100.3020) Image processing : Image reconstruction-restoration
(110.5120) Imaging systems : Photoacoustic imaging
(170.5120) Medical optics and biotechnology : Photoacoustic imaging

Mingjian Sun, Naizhang Feng, Yi Shen, Jiangang Li, Liyong Ma, and Zhenghua Wu, "Photoacoustic image reconstruction based on Bayesian compressive sensing algorithm," Chin. Opt. Lett. 9, 061002- (2011)

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