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14 November 2021 Digital high-speed compressed sensing photoacoustic imaging simulation platform based on K-Wave
Zihao Li, Xianlin Song, Aojie Zhao
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Proceedings Volume 11914, SPIE Future Sensing Technologies 2021; 119141G (2021) https://doi.org/10.1117/12.2612457
Event: SPIE Future Sensing Technologies, 2021, Online Only
Abstract
The k-wave toolbox is used to construct a compressed-sensing-based photoacoustic imaging model. And the image is reconstructed by the Jacques Hadamard Observation Matrix and the two reconstruction algorithms (OMP and ROMP). The restored image contains the main information of the original image from the visual and PSNR value, it means that the original image can be restored by the combination of Compressed Sensing theory and suitable de-noising method. Compared with Nyquist's sampling method, the amount of data collected by our compressed sensing theory is greatly reduced, which saves resources and space to a great extent. This theory has a great advantage for the photoacoustic imaging of big data, and also can provide the convenience of time for the following image analysis. By the way, it's been experimentally determined that the ROMP reconstruction algorithm has a better reconstruction effect than OMP reconstruction algorithm does.
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Zihao Li, Xianlin Song, and Aojie Zhao "Digital high-speed compressed sensing photoacoustic imaging simulation platform based on K-Wave", Proc. SPIE 11914, SPIE Future Sensing Technologies 2021, 119141G (14 November 2021); https://doi.org/10.1117/12.2612457
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KEYWORDS
Compressed sensing
Photoacoustic tomography
Photoacoustic spectroscopy
MATLAB
Photoacoustic imaging
Reconstruction algorithms
Virtual reality
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