A Spectral CT Method to Directly Estimate Basis Material Maps From Experimental Photon-Counting Data

The proposed spectral CT method solves the constrained one-step spectral CT reconstruction (cOSSCIR) optimization problem to estimate basis material maps while modeling the nonlinear X-ray detection process and enforcing convex constraints on the basis map images. In order to apply the optimization-...

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Published in:IEEE transactions on medical imaging 2017-09, Vol.36 (9), p.1808-1819
Main Authors: Schmidt, Taly Gilat, Barber, Rina Foygel, Sidky, Emil Y.
Format: Article
Language:English
Subjects:
Algorithms
Aluminum
Calibration
Computed tomography
Computer simulation
Data models
Detectors
Energy measurement
Errors
Feasibility studies
Image detection
Image reconstruction
Iterative reconstruction
Low density polyethylenes
material decomposition
Mathematical models
Modelling
Muscles
Optimization
Parameters
Phantoms, Imaging
photon-counting
Photonics
Photons
Polyethylene
Polymethyl methacrylate
Polymethylmethacrylate
Polytetrafluoroethylene
Scaling
Spectra
spectral CT
Tissues
Tomography, X-Ray Computed
X-Rays
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cited_by cdi_FETCH-LOGICAL-c557t-ab2ac3092461c250d786cee1f261d80e5d44a352f8b61a6e7510edceddacb7453
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description The proposed spectral CT method solves the constrained one-step spectral CT reconstruction (cOSSCIR) optimization problem to estimate basis material maps while modeling the nonlinear X-ray detection process and enforcing convex constraints on the basis map images. In order to apply the optimization-based reconstruction approach to experimental data, the presented method empirically estimates the effective energy-window spectra using a calibration procedure. The amplitudes of the estimated spectra were further optimized as part of the reconstruction process to reduce ring artifacts. A validation approach was developed to select constraint parameters. The proposed spectral CT method was evaluated through simulations and experiments with a photon-counting detector. Basis material map images were successfully reconstructed using the presented empirical spectral modeling and cOSSCIR optimization approach. In simulations, the cOSSCIR approach accurately reconstructed the basis map images (
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For the Teflon region, the experimental results demonstrated 8% and 31% error in the PMMA and aluminum basis material maps, respectively, compared with -24% and 126% error without estimation of the effective energy window spectra, with residual errors likely due to insufficient modeling of detector effects. The cOSSCIR algorithm estimated the material decomposition angle to within 1.3 degree error, where, for reference, the difference in angle between PMMA and muscle tissue is 2.1 degrees. The joint estimation of spectral-response scaling coefficients and basis material maps was found to reduce ring artifacts in both a phantom and tissue specimen. 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source IEEE Electronic Library (IEL) Journals
subjects Algorithms
Aluminum
Calibration
Computed tomography
Computer simulation
Data models
Detectors
Energy measurement
Errors
Feasibility studies
Image detection
Image reconstruction
Iterative reconstruction
Low density polyethylenes
material decomposition
Mathematical models
Modelling
Muscles
Optimization
Parameters
Phantoms, Imaging
photon-counting
Photonics
Photons
Polyethylene
Polymethyl methacrylate
Polymethylmethacrylate
Polytetrafluoroethylene
Scaling
Spectra
spectral CT
Tissues
Tomography, X-Ray Computed
X-Rays
title A Spectral CT Method to Directly Estimate Basis Material Maps From Experimental Photon-Counting Data
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