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Proceedings Paper

Signal processing using wavelet transform in photoacoustic tomography
Author(s): Tao Lu; Jingying Jiang; Yixiong Su; Zhiyuan Song; Jiangquan Yao; Ruikang K. Wang
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Paper Abstract

In order to improve the imaging contrast and resolution in photoacoustic tomography(PAT), the deconvolution between the transducer impulse response and the recorded photoacoustic(PA) signal of the tissue phantom is often used. The suppression of noise is critical in the deconvolution. Compared with the traditional band-pass filter in Fourier domain, wiener filter is more appropriate for the wide band PA signal. The scaling parameter in wiener filter is hard to determine using the traditional Fourier domain method. To solve the problem, the deconvolution algorithm with wiener filter based on the wavelet transform is presented. The scaling parameter is estimated using discrete wavelet transform(DWT) by its multi-resolution analysis(MRA) ability. The white noise had been effectively suppressed. Both numerical simulation and experimental results demonstrated that the contrast and resolution of PA images had been improved.

Paper Details

Date Published: 7 February 2007
PDF: 6 pages
Proc. SPIE 6439, Optics in Tissue Engineering and Regenerative Medicine, 64390L (7 February 2007); doi: 10.1117/12.705738
Show Author Affiliations
Tao Lu, Tianjin Univ. (China)
Jingying Jiang, Tianjin Univ. (China)
Yixiong Su, Tianjin Univ. (China)
Zhiyuan Song, Tianjin Univ. (China)
Jiangquan Yao, Tianjin Univ. (China)
Ruikang K. Wang, Oregon Health and Science Univ. (United States)

Published in SPIE Proceedings Vol. 6439:
Optics in Tissue Engineering and Regenerative Medicine
Sean J. Kirkpatrick; Ruikang K. Wang, Editor(s)

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