Helsinki Tomography Challenge 2022 open tomographic dataset (HTC 2022)

This dataset is primarily designed for the Helsinki Tomography Challenge 2022 (HTC 2022), but it can be used for generic algorithm research and development in limited angle tomography. The dataset contains 2D tomographic measurements, i.e. sinograms and the affiliated metadata containing measurement geometry and other specifications. The sinograms have already been pre-processed with background and flat-field corrections, and compensated for a slightly misaligned center of rotation in the cone-beam computed tomography scanner. The log-transforms from intensity measurements to attenuation data have also been already computed. The data has been stored as MATLAB structs and saved in .mat file format. The purpose of HTC 2022 is to develop algorithms for limited angle tomography. The challenge data consists of tomographic measurements of a set of plastic phantoms with a diameter of 7 cm and with holes of differing shapes cut into them. The data are arranged into seven different difficulty levels, labeled 1-7, with each level containing three different phantoms, labeled A-C. As the difficulty level increases, the number of holes increases and their shapes become increasingly complex. Furthermore, the view angle is reduced as the difficulty level increases, starting with a 90 degree field of view at level 1, and reducing by 10 degrees at each increasing level of difficulty. The current available dataset also contains five training phantoms with full angular data. These is designed to facilitate algorithm development and benchmarking for the challenge itself. Four of the phantoms contain holes. These are labeled ta, tb, tc, and td. A fifth phantom is a solid disc with no holes. We encourage subsampling these datasets to create limited data sinograms and comparing the reconstruction results to the ground truth obtainable from the full-data sinograms. The full data for all the phantoms will be released after the Helsinki Tomography Challenge 2022 has ended. All measurements were conducted at the Industrial Mathematics Computed Tomography Laboratory at the University of Helsinki.