Virtual compressed sensing photoacoustic tomography using BPDN algorithm based on k-space

Jing Wang; Bo Li; Aojie Zhao; Xianlin Song

doi:10.1117/12.2592183

20 June 2021 Virtual compressed sensing photoacoustic tomography using BPDN algorithm based on k-space

Jing Wang, Bo Li, Aojie Zhao, Xianlin Song

Proceedings Volume 11788, Digital Optical Technologies 2021; 117880I (2021) https://doi.org/10.1117/12.2592183
Event: SPIE Digital Optical Technologies, 2021, Online Only

Abstract

As a new imaging modality, photoacoustic imaging combines the advantages of optical imaging and ultrasonic imaging, which can provide deeper imaging depth and higher spatial resolution. At the same time, the high optical contrast between different tissues in photoacoustic images provides an important means for the study of biological tissue morphology, physiological and pathological characteristics. It has a very broad application prospect in the whole tissue structure and functional imaging. Therefore, it has been closely concerned in the field of biomedicine and has been developed rapidly in recent years. In the field of nuclear magnetic resonance (NMR), how to restore the original signal to be known with less measured values is an important research topic. In this paper, based on photoacoustic imaging technology and compression sensing reconstruction algorithm, a virtual simulation platform for compression sensing photoacoustic tomography is constructed by using k-wave simulation toolbox. Through this platform, a simulation model of photoacoustic propagation was established, we analyzed the photoacoustic signal generated by the simulation model. Finally, the basis pursuit denoising algorithm in the compressed sensing reconstruction algorithm is used to reconstruct the image of the vascular network. The results show that the virtual simulation platform successfully realizes the compressed sensing photoacoustic tomography with small amount of data but high reconstruction quality, which has practical significance and theoretical value for the research of the application of compress sensing in photoacoustic imaging.

Conference Presentation

Citation Download Citation

Jing Wang, Bo Li, Aojie Zhao, and Xianlin Song "Virtual compressed sensing photoacoustic tomography using BPDN algorithm based on k-space", Proc. SPIE 11788, Digital Optical Technologies 2021, 117880I (20 June 2021); https://doi.org/10.1117/12.2592183

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