Iori Gianluca, Foudeh Ibrahim, Alzu'bi Mustafa, Al Mohammad Malik, Matalgah Salman
SESAME - Synchrotron-light for Experimental Science and Applications in the Middle East, Allan, 19252, Jordan.
Open Res Eur. 2024 May 28;4:54. doi: 10.12688/openreseurope.16863.1. eCollection 2024.
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.
同步加速器X射线计算机断层扫描是一种无损三维成像技术,它能够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,以及保存样本的可能性,来自无数学科的科研用户对该技术的需求日益增加。计算机断层扫描重建是一个计算过程,通过该过程,实验射线照片在扫描后被转换为有意义的三维图像。该过程包括对原始数据进行图像背景和伪影校正的预处理步骤、近似逆拉东变换的重建步骤,以及将重建的体图像写入磁盘。有几个开源Python包可帮助科学家进行断层扫描重建,它们提供了利用中央处理器或图形处理器(分别为CPU和GPU)的重建算法的高效实现,并自动执行数据处理管道的大部分工作。通过在高性能计算(HPC)集群上调度和并行化要求较高的重建任务,可以进一步提高生产力。然而,目视检查和交互式选择最佳重建参数仍然是关键步骤,通常需要与数据的最终用户密切交互来执行。因此,重建任务涉及多个软件。为用户提供图形用户界面,以便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进行访问。我们提出了Alrecon,这是一个使用Solara构建的用于断层扫描重建的纯Python Web应用程序。Alrecon为用户提供了一个直观且响应式的环境,用于探索数据和定制重建管道。通过利用流行的三维图像可视化工具,并为在HPC资源上进行重建调度提供用户友好的界面,Alrecon保证了任何类型的束线用户的生产力和资源的有效利用。