Hyperspectral X-ray CT Voxelized TV reconstruction of a single, iodine-stained lizard head sample

<p><strong>Dataset description</strong></p> <p>These datasets are voxel based reconstructions of hyperspectral CT data using the Core Imaging Library (CIL).&nbsp; They are stored as NeXus&nbsp;files (derived from hdf5) which can be read in, visualised and manipulated using CIL.</p> <p>&nbsp;- PDHG_TV_1000_Sp_alpha_0.004.nxs</p> <p>Is the solution after 1000 iterations of PDHG with TV applied in the spatial domain.&nbsp;</p> <p>&nbsp;- PDHG_TV_1000_SpCh_alpha_0.003_beta_0.5.nxs</p> <p>Is the solution after 1000 iterations of PDHG with TV applied both in the spatial domain, and in the energy (channel) domain.&nbsp;</p> <p>&nbsp;</p> <p><strong>Dataset intended use</strong></p> <p>These datasets are used in the CIL training notebook:</p> <p>https://github.com/TomographicImaging/CIL-Demos/blob/main/examples/3_Multichannel/03_Hyperspectral_reconstruction.ipynb</p> <p>They can be imported using CIL, with the following code snippet:</p> <pre><code class="language-python">from cil.io import NEXUSDataReader reader = NEXUSDataReader(file_name='path/to/data/PDHG_TV_1000_Sp_alpha_0.004.nxs') data = reader.read()</code></pre> <p>&nbsp;</p>