Abstract
Optoacoustic tomography enables volumetric imaging with optical contrast in biological tissue at depths beyond the optical mean free path by the use of optical excitation and acoustic detection. The hybrid nature of optoacoustic tomography gives rise to two distinct inverse problems: The optical inverse problem, related to the propagation of the excitation light in tissue, and the acoustic inverse problem, which deals with the propagation and detection of the generated acoustic waves. Since the two inverse problems have different physical underpinnings and are governed by different types of equations, they are often treated independently as unrelated problems. From an imaging standpoint, the acoustic inverse problem relates to forming an image from the measured acoustic data, whereas the optical inverse problem relates to quantifying the formed image. This review focuses on the acoustic aspects of optoacoustic tomography, specifically acoustic reconstruction algorithms and imaging-system practicalities. As these two aspects are intimately linked, and no silver bullet exists in the path towards high-performance imaging, we adopt a holistic approach in our review and discuss the many links between the two aspects. Four classes of reconstruction algorithms are reviewed: time-domain (so called back-projection) formulae, frequency-domain formulae, time-reversal algorithms, and model-based algorithms. These algorithms are discussed in the context of the various acoustic detectors and detection surfaces which are commonly used in experimental studies. We further discuss the effects of non-ideal imaging scenarios on the quality of reconstruction and review methods that can mitigate these effects. Namely, we consider the cases of finite detector aperture, limited-view tomography, spatial under-sampling of the acoustic signals, and acoustic heterogeneities and losses.
Highlights
Over the past two decades, optoacoustic imaging has seen steady growth and has demonstrated notable capabilities to visualize living biological tissues with multiple applications emerging in both small-animal and clinical imaging [1,2,3,4,5,6,7,8,9,10]
We note that when complex acoustic propagation patterns exist due to acoustic impedance mismatches, e.g. acoustic waves guided in silica fibers [66], or angledependent reflection and refraction pattern which appear in piezoelectric transducers, the model used in Eq 11 loses its validity
Much of the diversity of optoacoustic imaging stems from its hybridity, as different patterns of optical excitation and acoustic detection lead to distinct imaging scenarios
Summary
Over the past two decades, optoacoustic imaging has seen steady growth and has demonstrated notable capabilities to visualize living biological tissues with multiple applications emerging in both small-animal and clinical imaging [1,2,3,4,5,6,7,8,9,10]. The tomographic detection of ultrasound is performed by either scanning a single detector, or detector array, around the imaged object or alternatively using multiple detectors to simultaneously capture the generated acoustic signals The latter configuration allows for ultrafast data acquisition, e.g. reconstruction of three-dimensional images from a single laser shot [24]. The application of optoacoustic tomography to imaging living objects presents major challenges to solving both the optical and acoustical inverse problems. As optoacoustic tomography has grown into a highly versatile imaging technology, the acoustic inverse problem represents a series of problems whose formulations depend on the specific implementation used Practical considerations such as high sensitivity, short imaging sessions, and geometrical compatibility to the imaged object often play a decisive role in the design of optoacoustic systems.
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