New software protocols for enabling laboratory based temporal CT

Parmesh Gajjar, Jakob Jorgensen, Jose Godinho, Christopher Johnson, Andrew Ramsey, Philip Withers

    Research output: Contribution to journalArticlepeer-review

    3 Downloads (Pure)


    Temporal micro-computed tomography (CT) allows the non-destructive quantification of processes that are evolving over time in 3D. Despite the increasing popularity of temporal CT, the practical implementation and optimisation can be difficult. Here, we present new software protocols that enable temporal CT using commercial laboratory CT systems. The first protocol drastically reduces the need for periodic intervention when making time-lapse experiments, allowing a large number of tomograms to be collected automatically. The automated scanning at regular intervals needed for uninterrupted time-lapse CT is demonstrated by analysing the germination of a mung bean (vigna radiata), whilst the synchronisation with an in situ rig required for interrupted time-lapse CT is highlighted using a shear cell to observe granular segregation. The second protocol uses golden-ratio angular sampling with an iterative reconstruction scheme and allows the number of projections in a reconstruction to be changed as sample evolution occurs. This overcomes the limitation of the need to know a priori what the best time window for each scan is. The protocol is evaluated by studying barite precipitation within a porous column, allowing a comparison of spatial and temporal resolution of reconstructions with different numbers of projections. Both of the protocols presented here have great potential for wider application, including, but not limited to, in situ mechanical testing, following battery degradation and chemical reactions.
    Original languageEnglish
    JournalReview of Scientific Instruments
    Early online date5 Sep 2018
    Publication statusPublished - 2018


    Dive into the research topics of 'New software protocols for enabling laboratory based temporal CT'. Together they form a unique fingerprint.

    Cite this