Sample data and Python code for the article: V. Di Trapani, L. Brombal, and F. Brun, Multi-material spectral photon-counting micro-CT with minimum residual decomposition and self-supervised deep denoising, Optics Express, Vol. 30, Issue 24, pp. 42995-43011 (2022).
Note: MR-BMD might require a few minutes on a modern multi-core machine for 512x512 images. An implementation of conventional multi-material BMD is also included in the repository for comparison.
Code requires as input a number (e.g. 8) of X-ray CT (Computed Tomography) images at different energies:
and a decomposition matrix resulting from the physics of the CT settings and the desired materials (e.g. 4):
Note: different number of energy bins and materials can be considered.
Known the pixel size, the code outputs the concentration map of each material in mg/ml, such as e.g.:
Note: in this example five materials were considered, i.e. soft tissue (water), bone, I, Ba, and Gd.