Optimal optoacoustic tomographic sampling is often hindered by the frequency-dependent directivity of ultrasound sensors, which can only be accounted for with an accurate 3-D model. Herein, we introduce a 3-D model-based reconstruction method applicable to optoacoustic imaging systems employing detection elements with arbitrary size and shape. The computational complexity and memory requirements are mitigated by introducing an efficient graphic processing unit (GPU)-based implementation of the iterative inversion. On-the-fly calculation of the entries of the model-matrix via a small look-up table avoids otherwise unfeasible storage of matrices typically occupying more than 300GB of memory. Superior imaging performance of the suggested method with respect to standard optoacoustic image reconstruction methods is first validated quantitatively using tissue-mimicking phantoms. Significant improvements in the spatial resolution, contrast to noise ratio and overall 3-D image quality are also reported in real tissues by imaging the finger of a healthy volunteer with a hand-held volumetric optoacoustic imaging system.
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Optimal optoacoustic tomographic sampling is often hindered by the frequency-dependent directivity of ultrasound sensors, which can only be accounted for with an accurate 3-D model. Herein, we introduce a 3-D model-based reconstruction method applicable to optoacoustic imaging systems employing detection elements with arbitrary size and shape. The computational complexity and memory requirements are mitigated by introducing an efficient graphic processing unit (GPU)-based implementation of the i...
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