[@Hsieh].

Discrete tomography is a powerful technique for dealing with such limited tomographic data. It can be applied if the object consists of only a limited number of materials with homogeneous densities. The Discrete Algebraic Reconstruction Technique (DART) [@DART1; @DART2] is an algebraic reconstruction method for discrete tomography that alternates between continuous reconstruction steps and discretization of the image intensities by segmentation. The DART algorithm has demonstrated to obtain higher image quality reconstructions with limited projections and angles compared to standard reconstruction methods. Numerous successive studies have improved the DART algorithm, which include automatic parameter estimation (PDM-DART [@PDMDART] and TVR-DART [@TVRDART]), multi-resolution reconstruction (MDART [@MDART]), relaxing voxel constraints (SDART [@SDART]) and adaptive boundary reconstructions (ADART [@ADART]). Nevertheless, a key limitation of DART is that it can only improve reconstruction quality if the number of different materials in the object is relatively small. The main reason is that for a larger number of materials, the segmentation step is no longer effective [@DART1; @DART2].

In some cases it is possible to obtain tomographic information in multiple measurements channels. For instance, in X-ray imaging the beams are typically polychromatic, i.e. X-ray photon energies are distributed over a spectrum. Each material in the object 