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Algorithm-Driven Advances for Scientific CT Instruments: From model-based to deep learning-based approaches
IEEE Signal Processing Magazine ( IF 14.9 ) Pub Date : 2021-12-28 , DOI: 10.1109/msp.2021.3123594
S.V. Venkatakrishnan , K. Aditya Mohan , Amir Koushyar Ziabari , Charles A. Bouman

Multiscale 3D characterization is widely used by materials scientists to further their understanding of the relationships between microscopic structure and macroscopic function. Scientific computed tomography (SCT) instruments are one of the most popular choices for 3D nondestructive characterization of materials at length scales ranging from the angstrom scale to the micron scale. These instruments typically have a source of radiation (such as electrons, X-rays, or neutrons) that interacts with the sample to be studied and a detector assembly to capture the result of this interaction (see Figure 1 ). A collection of such high-resolution measurements is made by reorienting the sample, which is mounted on a specially designed stage/holder after which reconstruction algorithms are used to produce the final 3D volume of interest. The specific choice of which instrument to use depends on the desired resolution and properties of the materials being imaged. The end goal of SCT scans includes determining the morphology, chemical composition, or dynamic behavior of materials when subjected to external stimuli. In summary, SCT instruments are powerful tools that enable 3D characterization across multiple length scales and play a critical role in furthering the understanding of the structure–function relationships of different materials.

中文翻译:

科学 CT 仪器的算法驱动进展:从基于模型的方法到基于深度学习的方法

材料科学家广泛使用多尺度 3D 表征来进一步了解微观结构和宏观功能之间的关系。科学计算机断层扫描 (SCT) 仪器是在从埃尺度到微米尺度的长度尺度上对材料进行 3D 无损表征的最受欢迎的选择之一。这些仪器通常具有与要研究的样品相互作用的辐射源(例如电子、X 射线或中子)和一个检测器组件以捕获这种相互作用的结果(参见图1 )。此类高分辨率测量的集合是通过重新定向样本来完成的,样本安装在专门设计的载物台/支架上,然后使用重建算法生成最终的 3D 感兴趣体积。使用哪种仪器的具体选择取决于所需的分辨率和被成像材料的特性。SCT 扫描的最终目标包括确定材料在受到外部刺激时的形态、化学成分或动态行为。总之,SCT 仪器是强大的工具,可以跨多个长度尺度进行 3D 表征,并在进一步了解不同材料的结构 - 功能关系方面发挥关键作用。
更新日期:2021-12-31
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