Limited-View Multi-Source Quantitative Photoacoustic Tomography
G. Hao; F. Jing; L. Song
刊名Inverse Problems
2015
英文摘要A limited-view scheme is proposed for multi-source quantitative photoacoustic tomography (MS-QPAT), in which the acoustic measurements following each optical illumination are acquired on the partial boundary near the optical source instead of the entire boundary, namely the limited-view MS-QPAT. The proposed limited-view scheme has an improved signal-to-noise ratio when the data are measured near the optical source, and reduces the acquisition time of the imaging system with a single or limited-view acoustic detector. A limited-view MS-QPAT example is to acquire 4° acoustic data following each of 90 optical illuminations, in contrast to 360° acoustic data for each of 90 optical illuminations under the conventional MS-QPAT setting. However, due to the incomplete data, the initial acoustic pressure can no longer be stably reconstructed that serves as an intermediate step in the conventional two-step reconstruction that first reconstructs the initial acoustic pressure and then the optical coefficients. Therefore the direct reconstruction of optical coefficients is considered using the coupled opto-acoustic forward model. The reconstruction algorithm is based on the quasi-Newton method, i.e. limited-memory BFGS with efficient adjoint computations of objective function gradients, and the sparsity-regularized formulation is also considered with tensor framelet sparsity transform and solved by the alternating direction method of multipliers.
收录类别SCI
原文出处iopscience.iop.org/0266-5611/31/6/065004
语种英语
内容类型期刊论文
源URL[http://ir.siat.ac.cn:8080/handle/172644/7065]  
专题深圳先进技术研究院_医工所
作者单位Inverse Problems
推荐引用方式
GB/T 7714
G. Hao,F. Jing,L. Song. Limited-View Multi-Source Quantitative Photoacoustic Tomography[J]. Inverse Problems,2015.
APA G. Hao,F. Jing,&L. Song.(2015).Limited-View Multi-Source Quantitative Photoacoustic Tomography.Inverse Problems.
MLA G. Hao,et al."Limited-View Multi-Source Quantitative Photoacoustic Tomography".Inverse Problems (2015).
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