  Many clinical applications depend critically on the accurate differentiation
and classification of different types of materials in patient anatomy. This
work introduces a unified framework for accurate nonlinear material
decomposition and applies it, for the first time, in the concept of
triple-energy CT (TECT) for enhanced material differentiation and
classification as well as dual-energy CT. The triple-energy data acquisition is
implemented at the scales of micro-CT and clinical CT imaging with commercial
"TwinBeam" dual-source DECT configuration and a fast kV switching DECT
configuration. Material decomposition and quantitative comparison with a photon
counting detector and with the presence of a bow-tie filter are also performed.
The proposed method provides quantitative material- and energy-selective images
examining realistic configurations for both dual- and triple-energy CT
measurements. Compared to the polychromatic kV CT images, virtual monochromatic
images show superior image quality. For the mouse phantom, quantitative
measurements show that the differences between gadodiamide and iodine
concentrations obtained using TECT and idealized photon counting CT (PCCT) are
smaller than 8 mg/mL and 1 mg/mL, respectively. TECT outperforms DECT for
multi-contrast CT imaging and is robust with respect to spectrum estimation.
For the thorax phantom, the differences between the concentrations of the
contrast map and the corresponding true reference values are smaller than 7
mg/mL for all of the realistic configurations. A unified framework for both
dual- and triple-energy CT imaging has been established for the accurate
extraction of material compositions; considering currently available commercial
DECT configurations. The novel technique is promising to provide an urgently
needed solution for several CT-based diagnosis and therapy applications.
