A high-throughput system for high-quality tomographic reconstruction of large datasets at Diamond Light Source

Abstract

Tomographic datasets collected at synchrotrons are becoming very large and complex, and, therefore, need to be managed efficiently. Raw images may have high pixel counts, and each pixel can be multidimensional and associated with additional data such as those derived from spectroscopy. In time-resolved studies, hundreds of tomographic datasets can be collected in sequence, yielding terabytes of data. Users of tomographic beamlines are drawn from various scientific disciplines, and many are keen to use tomographic reconstruction software that does not require a deep understanding of reconstruction principles. We have developed Savu, a reconstruction pipeline that enables users to rapidly reconstruct data to consistently create high-quality results. Savu is designed to work in an ‘orthogonal’ fashion, meaning that data can be converted between projection and sinogram space throughout the processing workflow as required. The Savu pipeline is modular and allows processing strategies to be optimized for users' purposes. In addition to the reconstruction algorithms themselves, it can include modules for identification of experimental problems, artefact correction, general image processing and data quality assessment. Savu is open source, open licensed and ‘facility-independent’: it can run on standard cluster infrastructure at any institution.

Three-Dimensional Cotton-Wool-Like Polyhydroxybutyrate/Siloxane-Doped Vaterite Composite Fibrous Scaffolds: Effect of Imogolite-Coating on Physicochemical and Cell Adhesion Properties

“…Samples were rotated from 0 to 180 • at a step of size of 0.05 • collecting in total 3,601 projections at 40 ms exposure. Projections were then reconstructed into 3D dataset using filtered back projection algorithm (Atwood et al, 2015). Obtained µCT data were then analyzed using Fiji R (Schindelin et al, 2012).…”

Fast Multi-scale imaging using the Beamline I13L at the Diamond Light Source

“…The beamline addresses a large user community for multi-scale and multi-modal science. User friendliness and ease for data analyses are implemented by the SAVU software pipeline [1] and in particular for ptychography by the PtyREX software [2]. Users may visit after experiments to conduct data analyses (visualisations, segmentations, measurements, etc.)…”

Reviewing GPU architectures to build efficient back projection for parallel geometries

“…Faster acquisition and a high level of automation is essential to study dynamic phenomena and at the same time enables experiments with significantly increased sample throughput. For example, in 2015 Diamond Light Source (DLS) reported that typically about 3000 scans are recorded during 5 days of operation at a single imaging beamline [7]. Consequently, the amount of data generated at imaging beamlines quickly grows and results in a steep rise of the required computing power.…”