DOI: 10.5281/zenodo.7081689
title: STEMPO - dynamic X-ray tomography phantom

description: The Spatio-TEmporal Motor-Powered (<strong>STEMPO</strong>) phantom is a physical phantom designed for collecting dynamic X-ray tomography data. The dynamic part of the phantom is computer controlled allowing for wide variety of different measurements and sampling setups to be used. The primary goal is to help mathematical community test and validate novel dynamic tomography reconstruction methods. Detailed documentation of the phantom, the included data and some examples can be found on the arXiv preprint: http://arxiv.org/abs/2209.12471. This data set can be appended with new data in the future. Current version (1.0) includes<br> <strong>Data - vol.1</strong> stempo_static_2d_b*.mat stempo_static_3d_b*.mat stempo_cont360_2d_b*.mat stempo_cont360_3d_b*.mat stempo_seq8x45_2d_b*.mat stempo_seq8x45_3d_b*.mat where b* denotes downsampling or binning of the data by a factor of (4, 8, 16 or 32). These are 2D and 3D data collected from a <em>static</em> object for reference, or from a dynamic target in a <em>continuous</em> 360 projection scan or <em>sequence</em> of 8 rotations, each consisting of 45 projections. In addition the data set contains <strong>Additional files</strong> stempo_ground_truth_2d_b4.mat which is an approximation of the true motion obtained from a single static FBP reconstruction which has been interpolated to match the location of the moving block during the <em>cont360</em> and <em>seq8x45</em> scans. Finally there are <strong>Example algorithms</strong> stempo_fbp_example.m stempo_fdk_example.m stempo_pdfp_wavelet_2d_example.m stempo_LplusS_2d_example.m which are short example algorithms of well know analytic (<em>FBP</em> and <em>FDK</em>) and iterative methods. <em>stempo_pdfp_wavelet_2d.m<strong> </strong></em>uses variational regularization and wavelet transform of the 2D + time object to reach a suitable solution. The codes are adapted from [1,2]. <em>stempo_LplusS_2d_example.m</em> attempts to split the reconstruction into low-rank component <em>L</em> and a sparse dynamic component <em>S</em>. This code is adapted from [3]. These are meant to give users ideas how the data can be used in different applications to match the requirements of different methods. Easiest way to utilize the data is with the ASTRA Toolbox and the HelTomo Toolbox. Some of the example codes also require Spot Linear Operator Toolbox (highly recommended) and the Wavelet Toolbox. However none of these are mandatory and any method (including programming languages other than MATLAB) are fine as long as the measurement geometry is respected.
description: The author is supported by the Emil Aaltonen Foundation junior researcher grant no. 200029 and the Vilho, Yrjö and Kalle Väisälä Foundation of the Finnish Academy of Science and Letters. The author also acknowledges the support of Academy of Finland through the Finnish Centre of Excellence in Inverse Modelling and Imaging 2018–2025, decision number 312339. Finally the author would like to thank E. Heikkilä, T. Heikkilä, A. Meaney and F.S. Moura for all their technical expertise and help in developing, building and imaging the mechanism.