Gatter, Ricarda; Bartzke, Gerhard; Madhusudhan, B N; Ahmed, Sharif; Clare, Michael A; Vardy, Mark E; Huhn, Katrin: Micro-computed tomography analysis of marine sediment samples of two piston cores, GS10-163-02PC (Norwegian fjord) and 64PE391-04 (offshore UK) [dataset]. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.979915 (dataset in review)

Two sediment samples (B043_20160307_SLS_1127_A3 and B052_20160307_SLS_1127_A5), taken from piston core GS10-163-02PC (66°10'57.358''N, 13°47'46.681''E; Vanneste et al., 2011; L'Heureux et al., 2012) at 2.95 metres below seafloor (mbsf) and 3.04 mbsf, respectively, and two sediment samples (B019_20160303_SLS_1127_B04 and B026_20160307_SLS_1127_A4), taken from piston core 64PE391-04 (61°15′40.679″N, 02°23′42.899″W; Gatter et al., 2020) at 9.18 mbsf and 9.25 mbsf depth, respectively, were scanned at the TOMCAT Beamline of the Swiss Light Source (SLS), Paul Scherrer Institute, Switzerland. A beam energy of 21 keV and a propagation distance of 81 mm were used to scan the samples. Per sample, 1501 projections (over 180° sample rotation) were recorded with an exposure time of 200 ms. The resultant micro-computed tomography (µCT) image stacks have a 3D voxel resolution of 0.325 µm (x-/y-/z-direction). Each reconstructed 3D image stack consists of 2160 individual 2D images (2560 x 2560 pixel). Images were reconstructed using the phase reconstruction algorithm described by Paganin et al. (2002). The data were processed using Fiji ImageJ (Schindelin et al., 2012) and Avizo 3D (version 2022.1). Within Fiji, the blurry edges that resulted from insufficient information for image reconstruction, were deleted from the datasets; thereby, the 2D image size was reduced from 2560 x 2560 pixel to 1730 x 1730 pixel. A first segmentation of solids and pores was performed using the Trainable Weka Segmentation 2D algorithm (Arganda-Carreras et al., 2017) within Fiji. The resultant binary images were used as input information for a second, more detailed, segmentation. In Avizo 3D, particles and pore space were segmented using a marker-based watershed algorithm and visualised in 3D. Subsequently, the sediment components were quantified using the 'Label Analysis' module in Avizo 3D.