This paper presents a novel method for the reconstruction of high-resolution
temporal images in dynamic tomographic imaging, particularly for discrete
objects with smooth boundaries that vary over time. Addressing the challenge of
limited measurements per time point, we propose a technique that
synergistically incorporates spatial and temporal information of the dynamic
objects. This is achieved through the application of the level-set method for
image segmentation and the representation of motion via a sinusoidal basis. The
result is a computationally efficient and easily optimizable variational
framework that enables the reconstruction of high-quality 2D or 3D image
sequences with a single projection per frame. Compared to current methods, our
proposed approach demonstrates superior performance on both synthetic and
pseudo-dynamic real X-ray tomography datasets. The implications of this
research extend to improved visualization and analysis of dynamic processes in
tomographic imaging, finding potential applications in diverse scientific and
industrial domains.

提出一种新方法，通过结合空间和时间信息，采用水平集方法和正弦基函数表达动态物体的运动，实现高分辨率时间图像的重建。与当前方法相比，在合成和伪动态真实 X 射线断层扫描数据集上表现出优越性能，为断层显像的动态过程提供改进的可视化和分析。