Dual-compressed photoacoustic single-pixel imaging
["Dual-compressed photoacoustic imaging with single-pixel detection enables high-efficiency surface tomography with 3D spatial resolution unlimited by the acoustics, revealing the potential for dynamic imaging in a scattering medium.","Photoacoustic imaging, an acoustic imaging modality with potentially optical resolution in an optical turbid medium, has attracted great attention. However, the convergence of wavefront optimization and raster scanning in computational photoacoustic imaging leads to the challenge of fast mapping, especially for a spatial resolution approaching the acoustic deep-subwavelength regime. As a sparse sampling paradigm, compressive sensing has been applied in numerous fields to accelerate data acquisition without significant quality losses. In this work, we propose a dual-compressed approach for photoacoustic surface tomography that enables high-efficiency imaging with 3D spatial resolution unlimited by the acoustics in a turbid environment. The dual-compressed photoacoustic imaging with single-pixel detection, enabled by spatially optical modulation with synchronized temporally photoacoustic coding, allows decoding of the fine optical information from the modulated acoustic signal even when the variance of original photoacoustic signals is weak. We perform a proof-of-principle numerical demonstration of dual-compressed photoacoustic imaging, that resolves acoustic sub-acoustic-wavelength details with a significantly reduced number of measurements, revealing the potential for dynamic imaging. The dual-compressed concept, which transforms unobtrusive spatial difference into spatio-temporal detectable information, can be generalized to other imaging modalities to realize efficient, high-spatial-resolution imaging."]
|WOS Research Area|
Science & Technology - Other Topics
|WOS Accession No|
Cited Times [WOS]:0
|Document Type||Journal Article|
|Department||Department of Materials Science and Engineering|
1.Department of Mechanical Engineering, University of Colorado, Boulder, CO80309, USA
2.Department of Mechanical Engineering, University of Colorado, Boulder, CO80309, USA
3.Department of Mechanical Engineering, University of Colorado, Boulder, CO80309, USA
Yuning,Guo,Baowen,Li,Xiaobo,Yin. Dual-compressed photoacoustic single-pixel imaging[J]. National Science Review,2022,10(1).
Yuning,Guo,Baowen,Li,&Xiaobo,Yin.(2022).Dual-compressed photoacoustic single-pixel imaging.National Science Review,10(1).
Yuning,Guo,et al."Dual-compressed photoacoustic single-pixel imaging".National Science Review 10.1(2022).
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