Work

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

Year: 2026

Type: article

Abstract: This study develops a sinogram-based material decomposition (MD) framework for a dual-energy cone-beam micro-computed tomography (micro-CT) system, providing quantitative spectral imaging without specialized photon-counting detectors. This work aims 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 calibration is performed in the image domain to ensure empirical accuracy, while the decomposition model is solved in the sinogram domain using a robust and computationally efficient Moore–Penrose pseudoinverse solver. By applying mass attenuation coefficients from a standard reference database to these basis maps, the framework synthesizes artifact-reduced virtual monochromatic images, photoelectric effect images (PEIs), and Compton scatter images (CSIs). Our results demonstrate that the framework, once calibrated, 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 within the object region. 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 hybrid MD method that enables quantitative, multi-material analysis on conventional micro-CT systems, offering a practical tool for advanced preclinical research.

Source: Biomedical Physics & Engineering Express

DOI: 10.1088/2057-1976/ae6f16

Authors: Shih-Chun Jin, Wei-Lin Li, Chieh Shen, Jyh-Cheng Chen

Institutions: National Yang Ming Chiao Tung University, Taipei Veterans General Hospital, National Taiwan University, China Medical University, China Medical University

Language: English

Topic: Advanced X-ray and CT Imaging

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,400

Funder: National Science and Technology Council