Systematic review on learning-based spectral CT
Spectral computed tomography (CT) has recently emerged as an advanced version of
medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two …
medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two …
Joint reconstruction of multi-channel, spectral CT data via constrained total nuclear variation minimization
DS Rigie, PJ La Riviere - Physics in Medicine & Biology, 2015 - iopscience.iop.org
We explore the use of the recently proposed'total nuclear variation'(TV N) as a regularizer for
reconstructing multi-channel, spectral CT images. This convex penalty is a natural extension …
reconstructing multi-channel, spectral CT images. This convex penalty is a natural extension …
Dual-contrast agent photon-counting computed tomography of the heart: initial experience
To determine the feasibility of dual—contrast agent imaging of the heart using photon-
counting detector (PCD) computed tomography (CT) to simultaneously assess both first …
counting detector (PCD) computed tomography (CT) to simultaneously assess both first …
Regularization of nonlinear decomposition of spectral x‐ray projection images
Purpose Exploiting the x‐ray measurements obtained in different energy bins, spectral
computed tomography (CT) has the ability to recover the 3‐D description of a patient in a …
computed tomography (CT) has the ability to recover the 3‐D description of a patient in a …
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 …
reconstruction (cOSSCIR) optimization problem to estimate basis material maps while …
[图书][B] First order algorithms in variational image processing
The success of non-smooth variational models in image processing is heavily based on
efficient algorithms. Taking into account the specific structure of the models as sum of …
efficient algorithms. Taking into account the specific structure of the models as sum of …
Material decomposition in spectral CT using deep learning: a Sim2Real transfer approach
The state-of-the art for solving the nonlinear material decomposition problem in spectral
computed tomography is based on variational methods, but these are computationally slow …
computed tomography is based on variational methods, but these are computationally slow …
Proximal ADMM for multi-channel image reconstruction in spectral X-ray CT
A Sawatzky, Q Xu, CO Schirra… - IEEE transactions on …, 2014 - ieeexplore.ieee.org
The development of spectral X-ray computed tomography (CT) using binned photon-
counting detectors has received great attention in recent years and has enabled selective …
counting detectors has received great attention in recent years and has enabled selective …
TICMR: Total image constrained material reconstruction via nonlocal total variation regularization for spectral CT
This work develops a material reconstruction method for spectral CT, namely Total Image
Constrained Material Reconstruction (TICMR), to maximize the utility of projection data in …
Constrained Material Reconstruction (TICMR), to maximize the utility of projection data in …
Image formation in spectral computed tomography
Spectral Computed Tomography (CT) aims at measuring the energy-resolved three-
dimensional (3D) distribution of the x-ray attenuation coefficients of a scanned object. It is …
dimensional (3D) distribution of the x-ray attenuation coefficients of a scanned object. It is …