Prohaszka Thomas, Neumann Lukas, Haltmeier Markus
Institute of Basic Sciences in Engineering Science, University of Innsbruck, Technikerstrasse 13, 6020 Innsbruck, Austria.
Department of Mathematics, University of Innsbruck Technikerstrasse 13, 6020 Innsbruck, Austria.
J Imaging. 2024 Apr 24;10(5):98. doi: 10.3390/jimaging10050098.
Image reconstruction in multispectral computed tomography (MSCT) requires solving a challenging nonlinear inverse problem, commonly tackled via iterative optimization algorithms. Existing methods necessitate computing the derivative of the forward map and potentially its regularized inverse. In this work, we present a simple yet highly effective algorithm for MSCT image reconstruction, utilizing iterative update mechanisms that leverage the full forward model in the forward step and a derivative-free adjoint problem. Our approach demonstrates both fast convergence and superior performance compared to existing algorithms, making it an interesting candidate for future work. We also discuss further generalizations of our method and its combination with additional regularization and other data discrepancy terms.
多光谱计算机断层扫描（MSCT）中的图像重建需要解决一个具有挑战性的非线性逆问题，通常通过迭代优化算法来处理。现有方法需要计算正向映射的导数以及可能的正则化逆。在这项工作中，我们提出了一种简单而高效的MSCT图像重建算法，利用迭代更新机制，在前向步骤中利用完整的正向模型和无导数伴随问题。与现有算法相比，我们的方法展示了快速收敛和卓越性能，使其成为未来工作的一个有趣候选方法。我们还讨论了我们方法的进一步推广及其与额外正则化和其他数据差异项的结合。
