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PHOTOACOUSTIC SIGNALS DENOISING BASED ON EMPIRICAL MODE DECOMPOSITION AND ENERGY-WINDOW METHOD

Department of Control Science and Engineering, Harbin Institute of Technology, 92 West Dazhi Street, Nan Gang District, Harbin, Heilongjiang 150001, China

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NAIZHANG FENG

Department of Control Science and Engineering, Harbin Institute of Technology, 92 West Dazhi Street, Nan Gang District, Harbin, Heilongjiang 150001, China

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YI SHEN

Department of Control Science and Engineering, Harbin Institute of Technology, 92 West Dazhi Street, Nan Gang District, Harbin, Heilongjiang 150001, China

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XIANGLI SHEN

Department of Control Science and Engineering, Harbin Institute of Technology, 92 West Dazhi Street, Nan Gang District, Harbin, Heilongjiang 150001, China

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, and

JIANGANG LI

Department of Control Science and Engineering, Harbin Institute of Technology, 92 West Dazhi Street, Nan Gang District, Harbin, Heilongjiang 150001, China

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https://doi.org/10.1142/S1793536912500045Cited by:16 (Source: Crossref)

Abstract

In the process of photoacoustic imaging (PAI), the photoacoustic signals are polluted by a strong background white noise, which is caused by many factors such as the system thermal noise or short noise, the tissue reflecting or scattering interference, and the impedance match lack between the transducer and tissue. The inevitable noise can degrade the contrast sensitivity of photoacoustic images seriously. In this paper, based on the energy window, a CMSE-EMD denoising method is employed to photoacoustic image reconstruction. Results of the simulation demonstrate that it can eliminate the image artifacts more effectively and achieve great improvement in image quality.

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References

A. O. Boudraa, J. C. Cexus and Z. Saidi, Int. J. Signal Process. 1, 11 (2004). Google Scholar
D. L. Donoho, IEEE Trans. Inform. Theory 41(3), 613 (1995). Crossref, Google Scholar
P. Flandrin, G. Rilling and P. Gonçalves, IEEE Signal Process. Lett. 11(2), 112 (2004). Crossref, Google Scholar
N. E. Huanget al., Proc. R. Soc. A, London 454, 903 (1998). Crossref, Google Scholar
Ku, G. (2004). Photoacoustic and Thermoacoustic Tomography: System Development for Biomedical Applications, Doctor Philosophy of Texas A&M University, Vol. 12, pp. 1–97 . Google Scholar
K. Maslovet al., Optic. Lett. 33, 929 (2008). Crossref, Google Scholar
Z. Renet al., Proc. of SPIE 7382, 1 (2009). Google Scholar
B. E. Treeby and B. T. Cox, J. Biomed. Optic. 15(2), 1 (2010). Google Scholar
L. V. Wang, J. Dis. Markers 19(3), 123 (2004). Crossref, Google Scholar
L. V. Wang, Med. Phys. 35(12), 5758 (2008). Crossref, Google Scholar