Real-time reconstruction and visualisation towards dynamic feedback control during time-resolved tomography experiments at TOMCAT

Abstract

Tomographic X-ray microscopy beamlines at synchrotron light sources worldwide have pushed the achievable time-resolution for dynamic 3-dimensional structural investigations down to a fraction of a second, allowing the study of quickly evolving systems. The large data rates involved impose heavy demands on computational resources, making it difficult to readily process and interrogate the resulting volumes. The data acquisition is thus performed essentially blindly. Such a sequential process makes it hard to notice problems with the measurement protocol or sample conditions, potentially rendering the acquired data unusable, and it keeps the user from optimizing the experimental parameters of the imaging task at hand. We present an efficient approach to address this issue based on the real-time reconstruction, visualisation and on-the-fly analysis of a small number of arbitrarily oriented slices. This solution, requiring only a single additional computing workstation, has been implemented at the TOMCAT beamline of the Swiss Light Source. The system is able to process multiple sets of slices per second, thus pushing the reconstruction throughput on the same level as the data acquisition. This enables the monitoring of dynamic processes as they occur and represents the next crucial step towards adaptive feedback control of time-resolved in situ tomographic experiments.

Fluorescence based rapid optical volume screening system (OVSS) for interrogating multicellular organisms

“…In contrast, OVSS requires an order-less data i.e., about 180 images and reatively less memory (few tens of MBs). So the availability of fast computing engines and an order-less sectional 2D data may enable volume reconstruction in real-time 52 , 53 .…”

Time Resolved in situ X-Ray Tomographic Microscopy Unraveling Dynamic Processes in Geologic Systems

“…The synchronization possibilities offered at TOMCAT (see Sections "Rotation Stage" and "Data Acquisition") at least partially mitigate this data deluge. The 3D preview currently under development (Buurlage et al, 2019) opens up new opportunities for an active experimental feedback and should enable smarter experiment control, thereby significantly reducing the amount of acquired data while maximizing its information content.…”

“…Although 2D X-ray projections of the sample already provide very insightful information to control and steer the experiment, for several applications they are unfortunately not sufficient to detect subtle but important changes indicating for instance the onset of a particular event. To expand the controlling and steering options, a previewing tool outputting selected arbitrarily oriented tomographic slices on-the-fly is currently being developed (Buurlage et al, 2019). This tool enables the optimization of the beamline and of experimental parameters as well as for instance the real-time selection of a region of interest in a larger volume, an operation often very difficult to achieve from 2D projections only.…”

Computational Imaging in 3D X-Ray Microscopy: Reconstruction, Image Segmentation and Time-Evolved Experiments

“…There is now a strong demand for improving data handling, analysis workflows and documentation of the results obtained from these techniques to truly enable correlative microscopy and material behavior characterization at multiple length scales. Furthermore, performing real-time reconstructions and segmentation of dynamically evolving features/classes in microstructures during an in situ experiment is gaining significant interest [28]. This capability would give the user complete knowledge of the dynamic evolution of the specimen under a stimulus (mechanical stresses, electrochemical environments etc.)…”