Optoacoustic Model-Based Inversion Using Anisotropic Adaptive Total-Variation Regularization
英文摘要：
In optoacoustic tomography, image reconstruction is often performed with incomplete or noisy data, leading to reconstruction errors. Significant improvement in reconstruction accuracy may be achieved in such cases by using nonlinear regularization schemes, such as total-variation minimization and $L_1$-based sparsity-preserving schemes. In this paper, we introduce a new framework for optoacoustic image reconstruction based on adaptive anisotropic total-variation regularization, which is more capable of preserving complex boundaries than conventional total-variation regularization. The new scheme is demonstrated in numerical simulations on blood-vessel images \textcolor{black} {as well as on experimental data} and is shown to be more capable than the total-variation-$L_1$ scheme in enhancing image contrast.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
