Characterizing impacts of model uncertainties in quantitative photoacoustics
For researchers in photoacoustic imaging, this provides a framework to characterize how uncertainties in model parameters affect reconstruction accuracy, though the results are preliminary and based on synthetic data.
This work quantifies the impact of model parameter uncertainties on the accuracy of reconstructed optical properties in quantitative photoacoustic imaging, deriving analytical error bounds for simplified settings and developing a polynomial chaos expansion-based computational procedure for general settings. Numerical simulations with synthetic data demonstrate the approach.
This work is concerned with uncertainty quantification problems for image reconstructions in quantitative photoacoustic imaging (PAT), a recent hybrid imaging modality that utilizes the photoacoustic effect to achieve high-resolution imaging of optical properties of tissue-like heterogeneous media. We quantify mathematically and computationally the impact of uncertainties in various model parameters of PAT on the accuracy of reconstructed optical properties. We derive, via sensitivity analysis, analytical bounds on error in image reconstructions in some simplified settings, and develop a computational procedure, based on the method of polynomial chaos expansion, for such error characterization in more general settings. Numerical simulations based on synthetic data are presented to illustrate the main ideas.