X-Ray based computed tomography (CT) is a well-established technique for determining the three-dimensional structure of an object from its two-dimensional projections. In the past few decades, there have been significant advancements in the brightness and detector technology of tomography instruments at synchrotron sources. These advancements have led to the emergence of new observations and discoveries, with improved capabilities such as faster frame rates, larger fields of view, higher resolution, and higher dimensionality. These advancements have enabled the material science community to expand the scope of tomographic measurements towards increasingly in-situ and in-operando measurements. In these new experiments, samples can be rapidly evolving, have complex geometries, and restrictions on the field of view, limiting the number of projections that can be collected. In such cases, standard filtered back-projections (FBP) for the reconstructions often result in poor-quality reconstructions. Iterative reconstruction algorithms, such as model-based iterative reconstructions (MBIR), have demonstrated considerable success in producing high-quality reconstructions under such restrictions, but typically require high-performance computing resources with hundreds of compute nodes to solve the problem in a reasonable time.

翻译：基于X射线的计算机断层扫描（CT）是一种成熟的技术，用于从物体的二维投影确定其三维结构。过去几十年来，同步辐射光源的断层扫描仪器在亮度和探测器技术方面取得了显著进展。这些进步催生了新的观测和发现，并提升了帧率、视场、分辨率和维度等能力。这些进步使材料科学界能够将断层测量范围扩展到日益增多的原位和操作中测量。在这些新实验中，样品可能快速演变、具有复杂几何形状，且视场受限，从而限制了可采集投影的数量。在这种情况下，用于重建的标准滤波反投影（FBP）通常会导致质量较差的重建结果。迭代重建算法，如基于模型的迭代重建（MBIR），在此类限制下已被证明能够生成高质量的重建，但通常需要配备数百个计算节点的高性能计算资源才能在合理时间内完成求解。