  Optoacoustic (OA) imaging is a promising modality for quantifying blood
oxygen saturation (sO$_2$) in various biomedical applications - in diagnosis,
monitoring of organ function or even tumor treatment planning. We present an
accurate and practically feasible real-time capable method for quantitative
imaging of sO$_2$ based on combining multispectral (MS) and multiple
illumination (MI) OA imaging with learned spectral decoloring (LSD). For this
purpose we developed a hybrid real-time MI MS OA imaging setup with ultrasound
(US) imaging capability; we trained gradient boosting machines on MI spectrally
colored absorbed energy spectra generated by generic Monte Carlo simulations,
and used the trained models to estimate sO$_2$ on real OA measurements. We
validated MI-LSD in silico and on in vivo image sequences of radial arteries
and accompanying veins of five healthy human volunteers. We compared the
performance of the method to prior LSD work and conventional linear unmixing.
MI-LSD provided highly accurate results in silico and consistently plausible
results in vivo. This preliminary study shows a potentially high applicability
of quantitative OA oximetry imaging, using our method.
