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Abstract：
Synchrotron X-ray computed tomography is a non-destructive 3D imaging technique that offers the possibility to study the internal microstructure of samples with high spatial and temporal resolution. Given its unmatched image quality and acquisition speed, and the possibility to preserve the specimens, there is an increasing demand for this technique, from scientific users from innumerable disciplines. Computed tomography reconstruction is the computational process by which experimental radiographs are converted to a meaningful 3-dimensional image after the scan. The procedure involves pre-processing steps for image background and artifact correction on raw data, a reconstruction step approximating the inverse Radon-transform, and writing of the reconstructed volume image to disk. Several open-source Python packages exist to help scientists in the process of tomography reconstruction, by offering efficient implementations of reconstruction algorithms exploiting central or graphics processing unit (CPU and GPU, respectively), and by automating significant portions of the data processing pipeline. A further increase in productivity is attained by scheduling and parallelizing demanding reconstructions on high performance computing (HPC) clusters. Nevertheless, visual inspection and interactive selection of optimal reconstruction parameters remain crucial steps that are often performed in close interaction with the end-user of the data. As a result, the reconstruction task involves more than one software. Graphical user interfaces are provided to the user for fast inspection and optimization of reconstructions, while HPC resources are often accessed through scripts and command line interface. We propose Alrecon, a pure Python web application for tomographic reconstruction built using Solara. Alrecon offers users an intuitive and reactive environment for exploring data and customizing reconstruction pipelines. By leveraging upon popular 3D image visualization tools, and by providing a user-friendly interface for reconstruction scheduling on HPC resources, Alrecon guarantees productivity and efficient use of resources for any type of beamline user.
摘要：
同步加速器X射线计算机断层扫描是一种无损的3D成像技术，可以以高空间和时间分辨率研究样品的内部微观结构。鉴于其无与伦比的图像质量和采集速度，以及保存标本的可能性，对这种技术的需求越来越大，来自无数学科的科学用户。计算机断层扫描重建是在扫描后将实验X射线照片转换为有意义的3维图像的计算过程。该过程涉及图像背景的预处理步骤和对原始数据的伪影校正，近似反Radon变换的重建步骤，并将重建的卷映像写入磁盘。存在几个开源Python包，以帮助科学家在层析成像重建过程中，通过提供利用中央或图形处理单元(CPU和GPU，分别)，并通过自动化数据处理管道的重要部分。通过在高性能计算(HPC)集群上调度和并行化苛刻的重构,实现了生产率的进一步提高。然而，视觉检查和最佳重建参数的交互式选择仍然是关键步骤，通常与数据的最终用户密切互动。因此,重建任务涉及多个软件。图形用户界面提供给用户，用于快速检查和优化重建，而HPC资源通常通过脚本和命令行界面访问。我们提议Alrecon,使用Solara构建的用于断层摄影重建的纯PythonWeb应用程序。Alrecon为用户提供了一个直观和反应性的环境，用于探索数据和定制重建管道。通过利用流行的3D图像可视化工具，并通过为HPC资源上的重建调度提供用户友好的界面，Alrecon保证任何类型的光束线用户的生产力和资源的有效利用。
微计算机断层扫描（CT）是一种广泛已知的技术，采用X射线以高分辨率可视化样本的内部。通过称为CT重建的计算过程从CT扫描生成3D图像。Alrecon是一个现代的,用于CT重建的开源Web应用程序，设计保持非专家和新用户的CT技术。
微计算机断层扫描（CT）是一种广泛已知的技术，采用X射线以高分辨率可视化样本的内部。通过称为CT重建的计算过程从CT扫描生成3D图像。Alrecon是一个现代的,用于CT重建的开源Web应用程序，设计保持非专家和新用户的CT技术。
