Title | ||
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Rapid Three-dimensional Photoacoustic Imaging Reconstruction for Irregularly Layered Heterogeneous Media. |
Abstract | ||
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Photoacoustic imaging (PAI) is susceptible to speed of sound (SOS) differences in heterogeneous media which greatly reduce the resolutions and qualities of the imaging results. Several reconstruction methods have been reported to adapt for heterogenous media, but they are limited by specific deficiencies such as efficiency, accuracy, and model limitation problems. Among them, the plane wave model based on wavefield reconstruction is the most efficient and promising one for high-efficiency three-dimensional PAI. However, the classic plane wave model only suits for planar layered media, severely limiting its applications in practice. To this end, we modify the plane wave model to apply for irregularly layered heterogeneous media and propose a corresponding wavefield extrapolation to reconstruct photoacoustic image. This method employs split-step Fourier to compensate the SOS differences, extrapolates wavefields and reconstructs the image depth by depth. Furthermore, a floating discretization strategy is introduced to control and balance the efficiency and accuracy with a hyperparameter. The simulation and experiment results demonstrate that the proposed method can reconstruct the image with an equivalent resolution to time reversal’s and even have higher efficiency and robustness. To reconstruct a three-dimensional image with
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pixels, the proposed method takes only 5.5 seconds using a laptop loaded with
<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Intel(R) Core (TM) i7-8550U CPU @1.8GHz</italic>
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Year | DOI | Venue |
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2020 | 10.1109/TMI.2019.2940757 | IEEE transactions on medical imaging |
Keywords | DocType | Volume |
Image reconstruction,Media,Acoustics,Transducers,Mathematical model,Propagation,Imaging | Journal | 39 |
Issue | ISSN | Citations |
4 | 0278-0062 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
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Haoran Jin | 1 | 3 | 3.86 |
Ruochong Zhang | 2 | 1 | 3.77 |
Siyu Liu | 3 | 18 | 8.31 |
Yuanjin Zheng | 4 | 328 | 72.86 |