Polychromatic sinogram based material decomposition and reconstruction methods: Integrate standard reference database with an in-house cone-beam micro-computed tomography system

This study develops a sinogram-based material decomposition framework for a dual-energy cone-beam micro-CT system, providing quantitative spectral imaging without specialized photon-counting detectors. The aim is to address challenges in material characterization, particularly for preclinical in-vivo imaging. The methodology involves acquiring dual-energy projections (50 and 80 kVp) of a standardized reference phantom to calibrate a three-material known basis model. This model is then solved in the sinogram domain using a robust and computationally efficient Moore-Penrose pseudoinverse solver to generate basis material maps. By integrating these maps with a reference database, the framework synthesizes artifact-reduced virtual monochromatic images by photoelectric effect images, and Compton scatter images. Our results demonstrate that the framework, calibrated once, is highly generalizable and can be reliably applied to other phantoms and complex in-vivo rat scans. The method achieved accurate, automated segmentation of skeletal structures from soft tissues in in-vivo data, which was quantitatively validated on phantoms with structural similarity index values approaching 1.0. The synthesis successfully separated physical attenuation mechanisms, isolating bone-dominant signals in PEIs and soft-tissue signals in CSIs. In conclusion, this study validates an accessible and robust sinogram-based MD method that enables quantitative, multi-material analysis on conventional micro-CT systems, offering a practical tool for advanced preclinical research.