Luistari X-Ray microtomography dataset

The dataset consists of X-ray microcomputed tomography image file (file format .png) packets (file format .tar) and 3D model reconstructions (file formats .stl, .ply) from imaging studies of human skeletal parts from the archaeological (600-1100 CE) Luistari cemetery, located in Eura, Finland. The imaged finds belong to the archaeological collections of the Finnish Heritage Agency.

The dataset includes 3D surface reconstructions and 2D model image captures of human teeth and bones (n=69 specimens in total), all in one zip file titled "Surface reconstructions" categorized in separate folders according to anatomical part. In addition to the original model ( .stl; larger file size), there is in most cases also a Laplace-smoothed version of the surface 3D model (.ply; smaller file size; "_lapl" in file name).

The folder "TAR files" contains all the source image files as .tar packages, each .tar package containing the .png files of one imaged specimen (i.e. tooth or bone; total n=73), categorized in separate sub folders according to skeletal element type. Most imaged skeletal elements are teeth.

The file or folder name, in most cases, gives the identification of the tooth using the nomenclature by Fédération dentaire internationale (fdi), followed by the Finnish Heritage Agency museum ID (type KM12345_6789_10) .

The imaging was conducted at the University of Helsinki X-ray Micro-CT laboratory during 2015-2016 using a Phoenix nanotom|s device. For tooth imaging, an operating voltage of 120 kV and current of 150 µA was used and 1 mm Al filter was placed in the beam. Each scan consisted of 1000 projection images with 2.5 s exposure time. The voxel size in the images varies from 8.33 µm to 11 µm depending on the sample size. Imaging of bones was performed with similar specifications, and resulted in higher voxel sizes. The 3D models were constructed using the Bruker CT Analyzer (CTAn) software and smoothed with Meshlab Laplacian smoothing (steps 3, 1D boundary smoothing, contangent weighting).