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Multispectral optoacoustic tomography requires image feedback in real-time to locate and identify relevant tissue structures during clinical interventions. Backprojection methods are commonly used for optoacoustic image reconstruction in real-time but only afford imprecise images due to oversimplified modelling assumptions. Herein, we present a deep learning framework, termed DeepMB, that infers optoacoustic images with state-of-the-art quality in 31 ms per image.
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