@article{BuchmannKaplanPowelletal., author = {Buchmann, Jens and Kaplan, Bernhard and Powell, Samuel and Prohaska, Steffen and Laufer, Jan}, title = {3D quantitative photoacoustic tomography using an adjoint radiance Monte Carlo model and gradient descent}, series = {Journal of Biomedical Optics}, volume = {24}, journal = {Journal of Biomedical Optics}, number = {6}, doi = {10.1117/1.JBO.24.6.066001}, pages = {066001}, abstract = {Quantitative photoacoustic tomography aims to recover maps of the local concentrations of tissue chromophores from multispectral images. While model-based inversion schemes are promising approaches, major challenges to their practical implementation include the unknown fluence distribution and the scale of the inverse problem. This paper describes an inversion scheme based on a radiance Monte Carlo model and an adjoint-assisted gradient optimization that incorporates fluence-dependent step sizes and adaptive moment estimation. The inversion is shown to recover absolute chromophore concentrations, blood oxygen saturation and the Gr{\"u}neisen parameter from in silico 3D phantom images for different radiance approximations. The scattering coefficient was assumed to be homogeneous and known a priori.}, language = {en} }