STEMPO - dynamic X-ray tomography phantom

The Spatio-TEmporal Motor-Powered (STEMPO) 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 (volume 1 only) 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 (1.2) includes
         Data - vol.1 (v1.0)

• 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
• stempo_data_geometries.csv

         Data - vol.2 (added in v1.2)

• stempo_seq8x180_2d_b*.mat
• stempo_seq8x180_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 static object for reference, or from a dynamic target in a continuous 360 projection scan or sequence of 8 rotations, each consisting of 45 or 180 projections (with seq8x45 and seq8x180 data respectively). Finally stempo_data_geometries.csv is a simple table containing the key parameters of the measurement geometry in text format. Note that the height of the phantom for volume 2 data is slightly different compared to volume 1, including the static scan (mostly relevant for comparing 3D reconstructions).

In addition the data set contains

         Additional files

• 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 cont360 and seq8x45 scans. Finally there are

         Example algorithms

• 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 (FBP and FDK) and iterative methods. stempo_pdfp_wavelet_2d.m uses variational regularization and wavelet transform of the 2D + time object to reach a suitable solution. The codes are adapted from [1,2]. stempo_LplusS_2d_example.m attempts to split the reconstruction into low-rank component L and a sparse dynamic component S. 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.

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.

The author also thanks O. Tapaninen for helping measure the data for vol.2.