An Extended Algebraic Reconstruction Technique (E-ART) for Dual Spectral CT

Abstract

Compared with standard computed tomography (CT), dual spectral CT (DSCT) has many advantages for object separation, contrast enhancement, artifact reduction, and material composition assessment. But it is generally difficult to reconstruct images from polychromatic projections acquired by DSCT, because of the nonlinear relation between the polychromatic projections and the images to be reconstructed. This paper first models the DSCT reconstruction problem as a nonlinear system problem; and then extend the classic ART method to solve the nonlinear system. One feature of the proposed method is its flexibility. It fits for any scanning configurations commonly used and does not require consistent rays for different X-ray spectra. Another feature of the proposed method is its high degree of parallelism, which means that the method is suitable for acceleration on GPUs (graphic processing units) or other parallel systems. The method is validated with numerical experiments from simulated noise free and noisy data. High quality images are reconstructed with the proposed method from the polychromatic projections of DSCT. The reconstructed images are still satisfactory even if there are certain errors in the estimated X-ray spectra.

A GPU-based multi-resolution approach to iterative reconstruction algorithms in x-ray 3D dual spectral computed tomography

“…The DSCT basis material decomposition problem can be expressed as solving two basis materials images   f x and   g x of the scanned object from the measured high-energy polychromatic projections   1 pL and low-energy polychromatic projections   2 pL as follows [24]:…”

“…Basically, these reconstruction methods can be classified into two classes: direct approximation algorithms [11]- [15] and iterative algorithms [16]- [24]. Direct approximation algorithms require neither the knowledge of the x-ray spectrum nor of the energy-dependent attenuation coefficients, and allow a 2 faster material decomposition, but their reconstructed material density images suffer from beam hardening artifacts due to errors introduced in the calibration process of material decomposition.…”

“…Extended algebraic reconstruction technique (E-ART) is one of dual energy iterative algorithms [24]. The E-ART algorithm models the DSCT reconstruction problem as a nonlinear system problem, and then extends the classic ART algorithm to solve the nonlinear system.…”

TICMR: Total Image Constrained Material Reconstruction via Nonlocal Total Variation Regularization for Spectral CT

“…In contrast, the material compositions can also be reconstructed in a one-step procedure, i.e., the direct material reconstruction from multi-energy projection data [7], [21]–[24]. For that purpose, the spectral image dependence of the materials is often linearly modeled, i.e., for dual-energy CT [21], [22], [24] or multi-energy CT [7], [23], during which either energy-independent density and material volume fraction can be both explicitly modeled or their product [22], [23], i.e., the material composition, needs to be reconstructed [7], [21], [24].…”

“…For that purpose, the spectral image dependence of the materials is often linearly modeled, i.e., for dual-energy CT [21], [22], [24] or multi-energy CT [7], [23], during which either energy-independent density and material volume fraction can be both explicitly modeled or their product [22], [23], i.e., the material composition, needs to be reconstructed [7], [21], [24]. The explicit model of both energy-independent density and material volume fraction was introduced for beam hardening correction purpose [22] or when the number of energies is less than the number of materials [22], [23], for which additional steps may be needed, such as image segmentation and nonoverlapping material assumption [22].…”