High spatial resolution is a central aspect of tomographic imaging. In photoacoustic tomography, this requires accurate models for acoustic wave propagation and corresponding efficient image reconstruction methods. In this article we consider such models accounting for frequency dependent attenuation according to a wide class of attenuation laws that may include memory. We formulate the inverse problem of photoacoustic tomography in attenuating medium as ill-posed operator equation in a Hilbert space framework that is tackled by iterative regularization methods. For that purpose we derive explicit expressions for the adjoint problem that can efficiently be implemented. Our approach comes with a clear convergence analysis that is not shared by existing approaches for the considered model class. In contrast to time reversal the employed adjoint wave equation is again damping and thus has a stable solution. This stability property can be clearly seen in our numerical results. Indeed, if the attenuation is not too strong then the reconstruction results are even better than in the absence of attenuation. Moreover, the presented numerical results clearly demonstrate the efficiency and accuracy of the derived iterative reconstruction algorithms in various situations including the limited view case, where alternative methods cannot be directly applied.
Photoacoustic (PA) imaging, also called optoacoustic imaging, is a new biomedical imaging modality based on the use of laser-generated ultrasound that has emerged over the last decade. It is a hybrid modality, combining the high-contrast and spectroscopic-based specificity of optical imaging with the high spatial resolution of ultrasound imaging. In essence, a PA image can be regarded as an ultrasound image in which the contrast depends not on the mechanical and elastic properties of the tissue, but its optical properties, specifically optical absorption. As a consequence, it offers greater specificity than conventional ultrasound imaging with the ability to detect haemoglobin, lipids, water and other light-absorbing chomophores, but with greater penetration depth than purely optical imaging modalities that rely on ballistic photons. As well as visualizing anatomical structures such as the microvasculature, it can also provide functional information in the form of blood oxygenation, blood flow and temperature. All of this can be achieved over a wide range of length scales from micrometres to centimetres with scalable spatial resolution. These attributes lend PA imaging to a wide variety of applications in clinical medicine, preclinical research and basic biology for studying cancer, cardiovascular disease, abnormalities of the microcirculation and other conditions. With the emergence of a variety of truly compelling in vivo images obtained by a number of groups around the world in the last 2–3 years, the technique has come of age and the promise of PA imaging is now beginning to be realized. Recent highlights include the demonstration of whole-body small-animal imaging, the first demonstrations of molecular imaging, the introduction of new microscopy modes and the first steps towards clinical breast imaging being taken as well as a myriad of in vivo preclinical imaging studies. In this article, the underlying physical principles of the technique, its practical implementation, and a range of clinical and preclinical applications are reviewed.  Conventional image reconstruction methods for optoacoustic tomography (OAT) assume an idealized, nondispersive acoustic medium. However, the linear attenuation coefficient and the phase velocity of acoustic waves propagating in soft tissue depend on temporal frequency and satisfy a known dispersion law. These frequency-dependent effects are incorporated into an optoacoustic wave equation, and a corresponding reconstruction method for OAT is developed. The improvement in image fidelity that can be achieved over conventional reconstruction methods is demonstrated by use of computer-simulation studies. In this work, we show how to incorporate attenuation into the optoacoustic tomography (OAT) imaging equation and develop a strategy for compensating for this attenuation during image reconstruction. In OAT, one exposes a sample to pulses of electromagnetic radiation that cause small amounts of heating in the specimen. The heating engenders thermal expansion which, in turn, gives rise to acoustic waves. The resulting acoustic pressure signal is generally measured by transducers arrayed around the object, and these data may be used to reconstruct images of the original electromagnetic absorption. Frequency-dependent absorption of the acoustic waves can lead to blurring and distortion in reconstructed images. We show that in the temporal frequency domain, the optoacoustic wave equation incorporating attenuation is equivalent to the inhomogeneous Helmholtz equation with a complex wave number. While some work has been done in other fields on directly solving Helmholtz equations with complex wave numbers, these are generally computationally intensive numerical approaches. We pursue a different approach, deriving an integral equation that relates the temporal optoacoustic signal at a given transducer location in the presence of attenuation to the ideal signal that would have been obtained in the absence of attenuation. This equation is readily discretized and the resulting linear system of equations involves a matrix that need only be inverted once, at which point the inverse can be used to correct all of the measured time signals prior to reconstruction by conventional methods.