Joint Reconstruction of Absorbed Optical Energy Density and Sound Speed Distribution in Photoacoustic Computed Tomography: A numerical Investigation

Kavli Affiliate: Lihong V. Wang

| First 5 Authors: Chao Huang, Kun Wang, Robert W. Schoonover, Lihong V. Wang, Mark A. Anastasio

| Summary:

Photoacoustic computed tomography (PACT) is a rapidly emerging bioimaging
modality that seeks to reconstruct an estimate of the absorbed optical energy
density within an object. Conventional PACT image reconstruction methods assume
a constant speed-of-sound (SOS), which can result in image artifacts when
acoustic aberrations are significant. It has been demonstrated that
incorporating knowledge of an object’s SOS distribution into a PACT image
reconstruction method can improve image quality. However, in many cases, the
SOS distribution cannot be accurately and/or conveniently estimated prior to
the PACT experiment. Because variations in the SOS distribution induce
aberrations in the measured photoacoustic wavefields, certain information
regarding an object’s SOS distribution is encoded in the PACT measurement data.
Based on this observation, a joint reconstruction (JR) problem has been
proposed in which the SOS distribution is concurrently estimated along with the
sought-after absorbed optical energy density from the photoacoustic measurement
data. A broad understanding of the extent to which the JR problem can be
accurately and reliably solved has not been reported. In this work, a series of
numerical experiments is described that elucidate some important properties of
the JR problem that pertain to its practical feasibility. To accomplish this,
an optimization-based formulation of the JR problem is developed that yields a
non-linear iterative algorithm that alternatingly updates the two image
estimates. Heuristic analytic insights into the reconstruction problem are also
provided. These results confirm the ill-conditioned nature of the joint
reconstruction problem that will present significant challenges for practical
applications.

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