Abstract
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).
Abstract (translated)
随着微CT技术不断完善材料微观结构的表征，工业CT超精密检测生成的数据集越来越大，这要求在3D缺陷表征的精度和效率之间找到一个平衡点。本文提供了一个独特的视角，探讨了使用Micro-CT进行准确且高效三维可视化的近期进展，并追踪其从医学成像到工业无损检测（NDT）的应用历程。在这众多的CT重建与体积渲染方法中，文章精选并分析了一些能够兼顾精度和效率的方法，为研究者提供了一种全面而快速掌握高效的3D重构方法以表征微观特征的方式。 本文通过比较计算断层成像的基本原理和微结构技术的进步，探讨了从解析法到深度学习算法的CT重建算法的发展历程，并且还审视了体积渲染算法改进、加速以及数据缩减方面的进展。此外，它还探索了用于高精度、逼真高效体积渲染的先进照明模型。 最后，本文展望了CT重建和体积渲染未来可能的发展方向，旨在指导未来的科研工作迅速选择有效而准确的方法，并为通过虚拟与物理交互实现材料内部缺陷实时在线监测的新理念及方法开发提供启示，以便将数字孪生模型应用于结构健康监测（SHM）。
URL
https://arxiv.org/abs/2601.15098
