Due to modeling and experimental imperfections, multispectral optoacoustic tomography images are often afflicted with negative values, which are further amplified when propagating into the spectrally unmixed images of chromophore concentrations. Since negative values have no physical meaning, accuracy can potentially be improved by imposing non-negativity constraints on the initial reconstructions and the unmixing steps. Herein, we compare several non-negative constrained approaches with reconstruction and spectral unmixing performed separately or combined in a single inverse step. The quantitative performance and sensitivity of the different approaches in detecting small amounts of spectrally-distinct chromophores are studied in tissue-mimicking phantoms and mouse experiments.
Limited-view artefacts affect most optoacoustic (photoacoustic) imaging systems due to geometrical constraints that impede achieving full tomographic coverage as well as limited light penetration into scattering and absorbing objects. Indeed, it has been theoretically established and experimentally verified that accurate optoacoustic images can only be obtained if the imaged sample is fully enclosed (< π angular coverage) by the measuring locations. Since in many cases full angular coverage cannot be achieved, the visibility of structures along certain orientations is hampered. These effects are of particular relevance in the case of hand-held scanners with the imaged volume only accessible from one side. Herein, a new approach termed dynamic particle-enhanced optoacoustic tomography (DPOT) is described for accurate structural imaging in limited-view scenarios. The method is based on the non-linear combination of a sequence of tomographic reconstructions representing sparsely distributed moving particles. Good performance of the method is demonstrated in experiments consisting of dynamic visualization of flow of suspended microspheres in three-dimensions. The method is expected to be applicable for improving accuracy of angiographic optoacoustic imaging in living organisms.
In order to achieve real-time image rendering, optoacoustic tomography reconstructions are commonly done with back-projection algorithms due to their simplicity and low computational complexity. However, model-based algorithms have been shown to attain more accurate reconstruction performance due to their ability to model arbitrary detection geometries, transducer shapes and other experimental factors. The high computational complexity of the model-based schemes makes it challenging to be implemented for real time inversion. Herein, we introduce a novel discretization method for model-based optoacoustic tomography that enables its efficient parallel implementation on graphics processing units with extremely low memory overhead. We demonstrate that, when employing a tomographic scanner with 256 detectors, the new method achieves model-based optoacoustic inversion at 20 frames per second for a 200 × 200 image grid.
In optoacoustic tomography, images representing the light absorption distribution are reconstructed from the measured acoustic pressure waves at several locations around the imaged sample. Most reconstruction algorithms typically yield negative absorption values due to modelling inaccuracies and imperfect measurement conditions. Those negative optical absorption values have no physical meaning and their presence hinders image quantification and interpretation of biological information. We investigate herein the performance of optimization methods that impose non-negative constraints in model-based optoacoustic inversion. Specifically, we analyze the effects of the non-negative restrictions on image quality and accuracy as compared to the unconstrained approach. An efficient algorithm based on the projected quasi-Newton scheme and the limitedmemory Broyden-Fletcher-Goldfarb-Shannon method is used for the non-negative constrained inversion. We showcase that imposing non-negative constraints in model-based reconstruction leads to a quality increase in cross-sectional tomographic optoacoustic images.
Over the last decade fluorescent reporter technologies (both fluorescent probes and proteins) have become a
very powerful imaging tool in everyday biomedical research. Multispectral optoacoustic tomography (MSOT)
is an emerging imaging technology that can resolve fluorophore concentration in small animals situated in deep
tissue by multispectral acquisition and processing of optoacoustic signals. In this work, we study the optimum
operating conditions of MSOT in imaging fluorescence activity in small animals. The performance of various
fluorochromes / fluorescent proteins is examined and it is shown that the new infrared fluorescent protein is an
order of magnitude brighter than the red ones. Finally, wavelength reduction after principle component analysis
shows, that accurate unmixing and 3D reconstruction of the distribution of fluorochromes is possible only with
2 or 3 wavelengths.
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