Forward-backward splitting method for quantitative photoacoustic tomography

Quantitative photoacoustic tomography (PAT) reconstructs optical maps using ultrasonic measurements, with improved resolution from conventional optical imaging due to significantly smaller acoustic scattering than optical scattering for detecting signals in depth. In this work, formulating quantitat...

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Bibliographic Details
Published in:Inverse problems 2014-12, Vol.30 (12), p.125012-125030
Main Authors: Zhang, Xue, Zhou, Weifeng, Zhang, Xiaoqun, Gao, Hao
Format: Article
Language:English
Subjects:
Convergence
image reconstruction
Inverse problems
Least squares method
numerical inverse problem
Photoacoustic effect
quantitative photoacoustic tomography
Regularization
Splitting
Tomography
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Summary:Quantitative photoacoustic tomography (PAT) reconstructs optical maps using ultrasonic measurements, with improved resolution from conventional optical imaging due to significantly smaller acoustic scattering than optical scattering for detecting signals in depth. In this work, formulating quantitative PAT as a nonlinear least-squares problem with l1-norm sparsity regularization, we develop an efficient gradient-based reconstruction algorithm using a forward-backward splitting method, and prove its convergence for such a nonconvex problem.
ISSN:0266-5611
1361-6420
DOI:10.1088/0266-5611/30/12/125012