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

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.Comment: 13 pages, submitted to IEEE Transactions on Computational Imagin

Discrete Imaging Models for Three-Dimensional Optoacoustic Tomography using Radially Symmetric Expansion Functions

Optoacoustic tomography (OAT), also known as photoacoustic tomography, is an emerging computed biomedical imaging modality that exploits optical contrast and ultrasonic detection principles. Iterative image reconstruction algorithms that are based on discrete imaging models are actively being developed for OAT due to their ability to improve image quality by incorporating accurate models of the imaging physics, instrument response, and measurement noise. In this work, we investigate the use of discrete imaging models based on Kaiser-Bessel window functions for iterative image reconstruction in OAT. A closed-form expression for the pressure produced by a Kaiser-Bessel function is calculated, which facilitates accurate computation of the system matrix. Computer-simulation and experimental studies are employed to demonstrate the potential advantages of Kaiser-Bessel function-based iterative image reconstruction in OAT

Numerical investigation of the effects of shear waves in transcranial photoacoustic tomography with a planar geometry

Using a recently developed reconstruction method for photoacoustic tomography (PAT) valid for a planar measurement geometry parallel to a layered medium, we investigate the effects of shear wave propagation in the solid layer upon the ability to estimate Fourier components of the object. We examine this ability as a function of the thickness of the layer supporting shear waves as well as of the incidence angle of the field in the planewave representation. Examples are used to demonstrate the importance of accounting for shear waves in transcranial PAT. Error measures are introduced to quantify the error found when omitting shear waves from the forward model in PAT

Simultaneous reconstruction of absorbed optical energy density and speed of sound distributions in photoacoustic computed tomography

An important and interesting question in photoacoustic computed tomography (PACT) is whether the absorbed optical energy density distribution, A(r), and the speed of sound distribution, c(r), can both be accurately determined from the measured photoacoustic data alone. However, in many cases c(r) is unknown or cannot be accurately estimated. Therefore, it would be practically beneficial if A(r) and c(r) can be jointly reconstructed from the measurements. In this work, we propose a reconstruction approach to the joint reconstruction of both properties in PACT

Photoacoustic computed tomography correcting for heterogeneity and attenuation

We report an investigation of image reconstruction in photoacoustic tomography for objects that possess heterogeneous material and acoustic attenuation distributions. When the object contains materials, such as bone and soft-tissue, that are modeled using power law attenuation models with distinct exponents, we demonstrate that the effects of acoustic attenuation due to the most strongly attenuating material can be compensated for if the attenuation of the other less attenuating material(s) are neglected. Experiments with phantom objects are presented to validated our findings

Geometrical optics limit of stochastic electromagnetic fields

A method is described which elucidates propagation of an electromagnetic field generated by a stochastic, electromagnetic source within the short wavelength limit. The results can be used to determine statistical properties of fields using ray tracing methods

Numerical investigation of the effects of shear waves in transcranial photoacoustic tomography with a planar geometry

Using a recently developed reconstruction method for photoacoustic tomography (PAT) valid for a planar measurement geometry parallel to a layered medium, we investigate the effects of shear wave propagation in the solid layer upon the ability to estimate Fourier components of the object. We examine this ability as a function of the thickness of the layer supporting shear waves as well as of the incidence angle of the field in the planewave representation. Examples are used to demonstrate the importance of accounting for shear waves in transcranial PAT. Error measures are introduced to quantify the error found when omitting shear waves from the forward model in PAT

Aberration correction for transcranial photoacoustic tomography of primates employing adjunct image data

A challenge in photoacoustic tomography (PAT) brain imaging is to compensate for aberrations in the measured photoacoustic data due to their propagation through the skull. By use of information regarding the skull morphology and composition obtained from adjunct x-ray computed tomography image data, we developed a subject-specific imaging model that accounts for such aberrations. A time-reversal-based reconstruction algorithm was employed with this model for image reconstruction. The image reconstruction methodology was evaluated in experimental studies involving phantoms and monkey heads. The results establish that our reconstruction methodology can effectively compensate for skull-induced acoustic aberrations and improve image fidelity in transcranial PAT