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In many practical optoacoustic imaging implementations, dimensionality of the tomographic problem is commonly reduced into two dimensions or 1-D scanning geometries in order to simplify technical implementation, improve imaging speed or increase signal-to-noise ratio. However, this usually comes at a cost of significantly reduced quality of the tomographic data, out-of-plane image artifacts, and overall loss of image contrast and spatial resolution. Quantitative optoacoustic image reconstruction implies therefore collection of point 3-D (volumetric) data from as many locations around the object as possible. Here, we propose and validate an accurate model-based inversion algorithm for 3-D optoacoustic image reconstruction. Superior performance versus commonly-used backprojection inversion algorithms is showcased by numerical simulations and phantom experiments.