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Published June 5, 2018 | Published + Accepted Version
Journal Article Open

Parameterized Joint Reconstruction of the Initial Pressure and Sound Speed Distributions for Photoacoustic Computed Tomography


Accurate estimation of the initial pressure distribution in photoacoustic computed tomography (PACT) depends on knowledge of the sound speed distribution. However, the sound speed distribution is typically unknown. Further, the initial pressure and sound speed distributions cannot both, in general, be stably recovered from PACT measurements alone. In this work, a joint reconstruction (JR) method for the initial pressure distribution and a low-dimensional parameterized model of the sound speed distribution is proposed. By employing a priori information about the structure of the sound speed distribution, both the initial pressure and sound speed can be accurately recovered. The JR problem is solved by use of a proximal optimization method that allows constraints and nonsmooth regularization functions for the initial pressure distribution. The gradients of the cost function with respect to the initial pressure and sound speed distributions are calculated by use of an adjoint state method that has the same per-iteration computational cost as calculating the gradient with respect to the initial pressure distribution alone. This approach is evaluated through two-dimensional computer-simulation studies for a small animal imaging model and by application to experimental in vivo measurements of a mouse.

Additional Information

© 2018, Society for Industrial and Applied Mathematics. Submitted: 24 October 2017. Accepted: 05 February 2018. Published online: 05 June 2018. This work was funded in part by NSF award DMS1614305 and NIH award R01EB01696304. Computations were performed using the facilities of the Washington University Center for High Performance Computing, which were partially provided through grant NCRR 1S10RR022984-01A1.

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Published - 17m1153649.pdf

Accepted Version - nihms-1015338.pdf


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August 19, 2023
October 18, 2023