As Micro-CT technology continues to refine its characterization of material microstructures, industrial CT ultra-precision inspection is generating increasingly large datasets, necessitating solutions to the trade-off between accuracy and efficiency in the 3D characterization of defects during ultra-precise detection. This article provides a unique perspective on recent advances in accurate and efficient 3D visualization using Micro-CT, tracing its evolution from medical imaging to industrial non-destructive testing (NDT). Among the numerous CT reconstruction and volume rendering methods, this article selectively reviews and analyzes approaches that balance accuracy and efficiency, offering a comprehensive analysis to help researchers quickly grasp highly efficient and accurate 3D reconstruction methods for microscopic features. By comparing the principles of computed tomography with advancements in microstructural technology, this article examines the evolution of CT reconstruction algorithms from analytical methods to deep learning techniques, as well as improvements in volume rendering algorithms, acceleration, and data reduction. Additionally, it explores advanced lighting models for high-accuracy, photorealistic, and efficient volume rendering. Furthermore, this article envisions potential directions in CT reconstruction and volume rendering. It aims to guide future research in quickly selecting efficient and precise methods and developing new ideas and approaches for real-time online monitoring of internal material defects through virtual-physical interaction, for applying digital twin model to structural health monitoring (SHM).

翻译：随着显微CT技术对材料微观结构表征能力的持续提升，工业CT超精密检测产生的数据集日益庞大，亟需解决超精密检测过程中缺陷三维表征精度与效率的权衡问题。本文针对显微CT高精度高效三维可视化的最新进展提供了独特视角，追溯了其从医学影像到工业无损检测的发展脉络。在众多CT重建与体绘制方法中，本文选择性地评述并分析了兼顾精度与效率的技术路径，通过系统梳理帮助研究者快速掌握适用于微观特征的高效精确三维重建方法。通过对比计算机断层成像原理与微结构技术的进步，本文考察了CT重建算法从解析方法到深度学习技术的演进，以及体绘制算法在加速与数据缩减方面的改进。此外，本文还探讨了实现高精度、照片级真实感与高效体绘制的先进光照模型。最后，本文展望了CT重建与体绘制领域的潜在发展方向，旨在为未来研究提供指引：快速选择高效精确的方法，通过虚拟-物理交互实现材料内部缺陷实时在线监测的新思路，以及数字孪生模型在结构健康监测中的应用。