Mitigation of artifacts due to isolated acoustic heterogeneities in photoacoustic computed tomography using a variable data truncation-based reconstruction method

Photoacoustic computed tomography (PACT) is an emerging computed imaging modality that exploits optical contrast and ultrasonic detection principles to form images of the absorbed optical energy density within tissue. If the object possesses spatially variant acoustic properties that are unaccounted for by the reconstruction method, the estimated image can contain distortions. While reconstruction methods have recently been developed to compensate for this effect, they generally require the object's acoustic properties to be known a priori. To circumvent the need for detailed information regarding an object's acoustic properties, we previously proposed a half-time reconstruction method for PACT. A half-time reconstruction method estimates the PACT image from a data set that has been temporally truncated to exclude the data components that have been strongly aberrated. However, this method can be improved upon when the approximate sizes and locations of isolated heterogeneous structures, such as bones or gas pockets, are known. To address this, we investigate PACT reconstruction methods that are based on a variable data truncation (VDT) approach. The VDT approach represents a generalization of the half-time approach, in which the degree of temporal truncation for each measurement is determined by the distance between the corresponding ultrasonic transducer location and the nearest known bone or gas void location. Computer-simulated and experimental data are employed to demonstrate the effectiveness of the approach in mitigating artifacts due to acoustic heterogeneities

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

Image reconstruction in transcranial photoacoustic computed tomography of the brain

Photoacoustic computed tomography (PACT) holds great promise for transcranial brain imaging. However, the strong reflection, scattering, attenuation, and mode-conversion of photoacoustic waves in the skull pose serious challenges to establishing the method. The lack of an appropriate model of solid media in conventional PACT imaging models, which are based on the canonical scalar wave equation, causes a significant model mismatch in the presence of the skull and thus results in deteriorated reconstructed images. The goal of this study was to develop an image reconstruction algorithm that accurately models the skull and thereby ameliorates the quality of reconstructed images. The propagation of photoacoustic waves through the skull was modeled by a viscoelastic stress tensor wave equation, which was subsequently discretized by use of a staggered grid fourth-order finite-difference time-domain (FDTD) method. The matched adjoint of the FDTD-based wave propagation operator was derived for implementing a back-projection operator. Systematic computer simulations were conducted to demonstrate the effectiveness of the back-projection operator for reconstructing images in a realistic three-dimensional PACT brain imaging system. The results suggest that the proposed algorithm can successfully reconstruct images from transcranially-measured pressure data and readily be translated to clinical PACT brain imaging applications

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

Special Section Guest Editorial: Celebrating the Exponential Growth of Optoacoustic/Photoacoustic Imaging

Guest editors introduce contributors to the Special Section Celebrating the Exponential Growth of Optoacoustic/Photoacoustic Imaging. We are pleased to introduce the contributions to this JBO Special Section entitled “Celebrating the Exponential Growth of Biomedical Optoacoustic/Photoacoustic Imaging.” This title was chosen to reflect the strong growth of the field over the last two and a half decades. The diversity of papers in this special section bears witness to this, with contributions that encompass numerical modelling, advanced instrumentation, functional imaging, clinical translation, and novel biomedical applications

Image reconstruction in photoacoustic tomography with heterogeneous media using an iterative method

There remains an urgent need to develop effective photoacoustic computed tomography (PACT) image recon- struction methods for use with acoustically inhomogeneous media. Transcranial PACT brain imaging is an im- portant example of an emerging imaging application that would benefit greatly from this. Existing approaches to PACT image reconstruction in acoustically heterogeneous media are limited to weakly varying media, are computationally burdensome, and/or make impractical assumptions regarding the measurement geometry. In this work, we develop and investigate a full-wave approach to iterative image reconstruction in PACT for media possessing inhomogeneous speed-of-sound and mass density distributions. A key contribution of the work is the formulation of a procedure to implement a matched discrete forward and backprojection operator pair, which facilitates the application of a wide range of modern iterative image reconstruction algorithms. This presents the opportunity to employ application-specific regularization methods to mitigate image artifacts due to mea- surement data incompleteness and noise. Our results establish that the proposed image reconstruction method can effectively compensate for acoustic aberration and reduces artifacts in the reconstructed image

Weighted expectation maximization reconstruction algorithms for thermoacoustic tomography

Thermoacoustic tomography (TAT) is an emerging imaging technique with potential for a wide range of biomedical imaging applications. In this correspondence, we propose an infinite family of weighted expectation maximization (EM) algorithms for reconstruction of images from temporally truncated TAT measurement data. The weighted EM algorithms are equivalent mathematically to the conventional EM algorithm, but are shown to propagate data inconsistencies in different ways. Using simulated and experimental TAT measurement data, we demonstrate that suitable choices of weighted EM algorithms can effectively mitigate image artifacts that are attributable to temporal truncation of the TAT data function