Computed Laminography for the study of biogenic structures in sediment cores: A step between two- and three-dimensional imaging

TitleComputed Laminography for the study of biogenic structures in sediment cores: A step between two- and three-dimensional imaging
Publication TypeJournal Article
Year of Publication2024
AuthorsDorador, J, Rodríguez-Tovar, FJ, Charidemou, MSJ, Miguez-Salas, O
JournalMarine Geology
Volume470
Pagination107267
ISSN0025-3227
KeywordsBioturbation, Deep-sea settings, Image treatment, Internal structures, Non-invasive techniques
Abstract

The study of trace fossils —ecological indicators of environmental parameters such as organic-matter content, oxygenation or sedimentation rate, among others— is a powerful tool for analysing cores from deep-sea sediment. However, the visualization of biogenic structures in soft sediment cores is commonly poor. This problem has usually been solved by using X-ray radiographs from core slabs, and later by non-destructive Computed Tomography (CT). Yet the latter requires complex processing and computer resources to deal with a vast dataset. Computed Laminography (CL) stands as an alternative, non-destructive technique able to manage a small amount of data, providing results similar to X-ray radiographs. This technique is frequently used in other disciplines (e.g. material sciences), but rarely applied in geosciences. In the present study, we explore the usefulness of CL for studying the ichnological content of modern deep-sea deposits from boxcores collected from the Porcupine Abyssal Plain (NE Atlantic). Additionally, we compare results from Linear CL (LCL) and Circumferential CL (CCL) to discuss which is recommended depending on the goal involved. The obtained results confirm the usefulness of CL for the ichnological analysis of sediment cores, with similar results from LCL and CCL. However, recommendations are made to resolve doubtful scenarios and to save time. In light of our findings, the use of CL as a non-destructive technique, calling for a much smaller dataset than CT, can be highly recommended for the study of ichnological content or other internal structures.

URLhttps://www.sciencedirect.com/science/article/pii/S0025322724000513
DOI10.1016/j.margeo.2024.107267