The standard approach for photoacoustic imaging with variable speed of sound is time reversal, which consists in solving a well-posed final-boundary value problem backwards in time. This paper investigates the iterative Landweber regularization algorithm, where convergence is guaranteed by standard regularization theory, notably also in cases of trapping sound speed or for short measurement times. We formulate and solve the direct and inverse problem on , what is common in standard photoacoustic imaging, but not for time-reversal algorithms, . We both the direct and adjoint photoacoustic operator an interior and an exterior equation . The prior is solved using a Galerkin scheme in space and finite difference discretization in time, while the latter boundary integral equation. We therefore use a BEM-FEM approach for numerical solution of the forward operators. We analyze this method, prove convergence, and provide numerical tests. Moreover, we compare the approach to time reversal.

Elastographic imaging is a widely used technique which can in principle be implemented on top of every imaging modality. In elastography, the specimen is exposed to a force causing local displacements in the probe, and imaging is performed before and during the displacement experiment. From the computed displacements material parameters can be deduced, which in turn can be used for clinical diagnosis. Photoacoustic imaging is an emerging image modality, which exhibits functional and morphological contrast. However, opposed to ultrasound imaging, for instance, it is considered a modality which is not suited for elastography, because it does not reveal speckle patterns. However, this is somehow counter-intuitive, because photoacoustic imaging makes available the whole frequency spectrum as opposed to single frequency standard ultrasound imaging. In this work, we show that in fact artificial speckle patterns can be introduced by using only a band-limited part of the measurement data. We also show that after introduction of artificial speckle patterns, deformation estimation can be implemented more reliably in photoacoustic imaging.

To obtain the initial pressure from the collected data on a planar sensor arrangement in photoacoustic tomography, there exists an exact analytic frequency-domain reconstruction formula. An efficient realization of this formula needs to cope with the evaluation of the data's Fourier transform on a nonequispaced mesh. We use the nonuniform fast Fourier transform to handle this issue and show its feasibility in three-dimensional experiments with real and synthetic data. This is done in comparison to the standard approach that uses linear, polynomial, or nearest neighbor interpolation. Moreover, we investigate the effect and the utility of flexible sensor location to make optimal use of a limited number of sensor points. The computational realization is accomplished by the use of a multidimensional nonuniform fast Fourier algorithm, where nonuniform data sampling is performed both in frequency and spatial domain. Examples with synthetic and real data show that both approaches improve image quality. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

This paper investigates photoacoustic tomography with two spatially varying acoustic parameters, the compressibility and the density. We consider the reconstruction of the absorption density parameter (imaging parameter of Photoacoustics) with complete and partial measurement data. We investigate and analyze three different numerical methods for solving the imaging problem and compare the results.

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