Gel phantom data for dynamic X-ray tomography
| dc.contributor.affiliation | University of Helsinki-Meaney, Alexander | |
| dc.contributor.author | Meaney, Alexander | |
| dc.date.accessioned | 2025-04-29T13:59:32Z | |
| dc.date.issued | 2020-03-05 | |
| dc.date.issued | 2020-03-05 | |
| dc.description | The gel phantom was constructed to simulate diffusion of liquids inside plant stems, namely the flow of iodine-based contrast agents used in high resolution tomographic X-ray imaging of plants. In order to test different reconstruction methods, this radiation resistant phantom with similar diffusion properties was constructed. A more detailed documentation can be found on arXiv: https://arxiv.org/abs/2003.02841 The phantom consists of a 50 ml Falcon test tube filled with agarose gel. After the agarose solidified, five cavities were made into the gel and filled with 20% sucrose solution to guarantee the diffusion by directing osmosis to the gel body. In addition densely punctured plastic straws were placed in the cavities to simulate cellular passages such as phloem plasmodesmata and to slow down the lateral diffusion. The primary measurements consisted of 17 consecutive time frames, with initial stage of no contrast agent followed by steady increase and diffusion into the gel body over time. Each round of measurements consist of 360 projections with a fanbeam microCT-scanner, but we used only the central plane of the cone beam, resulting in 2D fan beam geometry. Data is given in two different resolutions corresponding to reconstructions of size 256 x 256 or 512 x 512, (GelPhantomData_b4.mat and GelPhantomData_b2.mat respectively). In addition to the primary measurements, a more densely sampled measurements from the first time step and an additional 18th time step are provided in GelPhantom_extra_frames.mat. The measurements are stored in special data structures containing all the necessary metadata. In combination with the MATLAB toolboxes this allows for easy application of forward operators and reconstruction algorithms. This is demonstrated using the included example codes. These require ASTRA Toolbox, Spot Linear Operator Toolbox and HelTomo Toolbox (v1) for MATLAB. NOTE: Some of the metadata field names are different in HelTomo v2 and higher. Use of the data requires renaming (or adding) two fields in to the parameters: numDetectorsPost = numDetectors; effectivePixelSizePost = effectivePixelSize; Update: in v1.2 the data and example codes have been updated to match HelTomo v2.1 convention. For backwards compatibility (with Heltomo 1.0) the old medatadata field names remain. The full cone-beam measurements and corresponding documentation are available in Zenodo. | |
| dc.identifier | https://doi.org/10.5281/zenodo.7876521 | |
| dc.identifier.uri | https://datakatalogi.helsinki.fi/handle/123456789/4335 | |
| dc.rights.license | cc-by-4.0 | |
| dc.subject | Dynamic X-ray tomography | |
| dc.subject | Gel phantom | |
| dc.subject | Open dataset | |
| dc.title | Gel phantom data for dynamic X-ray tomography | |
| dc.type | dataset |