19 February 2018 Sparse-view photoacoustic tomography using virtual parallel-projections and spatially adaptive filtering
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To fully realize the potential of photoacoustic tomography (PAT) in preclinical and clinical applications, rapid measurements and robust reconstructions are needed. Sparse-view measurements have been adopted effectively to accelerate the data acquisition. However, since the reconstruction from the sparse-view sampling data is challenging, both of the effective measurement and the appropriate reconstruction should be taken into account. In this study, we present an iterative sparse-view PAT reconstruction scheme where a virtual parallel-projection concept matching for the proposed measurement condition is introduced to help to achieve the “compressive sensing” procedure of the reconstruction, and meanwhile the spatially adaptive filtering fully considering the a priori information of the mutually similar blocks existing in natural images is introduced to effectively recover the partial unknown coefficients in the transformed domain. Therefore, the sparse-view PAT images can be reconstructed with higher quality compared with the results obtained by the universal back-projection (UBP) algorithm in the same sparse-view cases. The proposed approach has been validated by simulation experiments, which exhibits desirable performances in image fidelity even from a small number of measuring positions.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yihan Wang, Yihan Wang, Tong Lu, Tong Lu, Wenbo Wan, Wenbo Wan, Lingling Liu, Lingling Liu, Songhe Zhang, Songhe Zhang, Jiao Li, Jiao Li, Huijuan Zhao, Huijuan Zhao, Feng Gao, Feng Gao, } "Sparse-view photoacoustic tomography using virtual parallel-projections and spatially adaptive filtering", Proc. SPIE 10494, Photons Plus Ultrasound: Imaging and Sensing 2018, 104944T (19 February 2018); doi: 10.1117/12.2291371; https://doi.org/10.1117/12.2291371

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