Accurate Reconstruction of Multiple Basis Images Directly From Dual Energy CT Data

Objective:
We develop optimization-based algorithms to accurately reconstruct multiple (
$>$
2) basis images directly from dual-energy (DE) data in CT.
Methods:
In medical and industrial CT imaging, some basis materials such as bone, metals, and contrast agents of interest are confined often spatially within regions in the image. Exploiting this observation, we develop an optimization-based algorithm to reconstruct, directly from DE data, basis-region images from which multiple (
$>$
2) basis images and virtual monochromatic images (VMIs) can be obtained over the entire image array.
Results:
We conduct experimental studies using simulated and real DE data in CT, and evaluate basis images and VMIs obtained in terms of visual inspection and quantitative metrics. The study results reveal that the algorithm developed can accurately and robustly reconstruct multiple (
$>$
2) basis images directly from DE data.
Conclusions:
The developed algorithm can yield accurate multiple (
$>$
2) basis images, VMIs, and physical quantities of interest from DE data in CT.
Significance:
The work may provide insights into the development of practical procedures for reconstructing multiple basis images, VMIs, and physical quantities from DE data in applications. The work can be extended to reconstruct multiple basis images in multi-spectral or photon-counting CT.