Three line trajectory X-ray tomography datasets of a small wooden block

Summary
This submission contains three tomographic datasets of a small wooden block.
The data is made available as part of [Bossema et al., 2021].  

Apparatus
The dataset is acquired using the custom-built and highly flexible CT scanner, FleX-ray Laboratory, developed by TESCAN-XRE, located at CWI in Amsterdam. This apparatus consists of a cone-beam microfocus X-ray point source that projects polychromatic X-rays onto a 1944-by-1536 pixels, 14-bit, flat detector panel. Full details can be found in [Coban 2020].
 
Sample Information
The sample is small wooden block of conifer wood (10x12x3cm).

Experimental Plan
The data in this submission was collected to compare CT (see Zenodo dataset 10.5281/zenodo.4533882) reconstructions to reconstructions obtained using a line trajectory (LT) scanning method and to investigate the effect of the orientation of the block on the LT reconstructions (see Figures 3 and 5 in [Bossema et al, 2021]).
The dataset consists of three LT datasets with the wood in different orientations.
All raw data (i.e. no corrections) is made available in .tif format.
 
List of Contents
The content of the submission is given below.

• LT_flat: 2201 projections, with the wood in orientation corresponding to fig. 4a in [Bossema et al., 2021]
• LT_upright: 2001 projections, with the wood in orientation corresponding to fig. 4b in [Bossema et al., 2021]
• LT_upfront: 2201 projections, with the wood in orientation corresponding to fig. 4c in [Bossema et al., 2021]

Each data folder contains:

• dark-field (or closed-shutter) image, di000000.tif,
• flat-field (or open-shutter) image before acquisition, io000000.tif, and after acquisition, io000001.tif,
• raw (unprocessed or uncorrected) projections, scan_*.tif,
• scan settings.txt, a text file with scanner metadata in more human readable format, and
• script_executed.txt, the text file containing the list of commands the apparatus has executed.

Additional Links
These datasets are produced by the Computational Imaging group at Centrum Wiskunde & Informatica (CI-CWI). For any relevant Python/MATLAB scripts for the FleX-ray datasets, we refer the reader to our group's GitHub page.
 
Contact Details
For more information or guidance in using these datasets, please get in touch with

•     bossema [at] cwi.nl

 
Acknowledgments
The authors would like to acknowledge the funding from the Netherlands Organisation for Scientific Research (NWO), project numbers 341-60-001, 639.073.506 and 628.007.033 and Netherlands Institute for Conservation, Art and Science (NICAS).