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 …
Tensor-based dictionary learning for spectral CT reconstruction
Spectral computed tomography (CT) produces an energy-discriminative attenuation map of
an object, extending a conventional image volume with a spectral dimension. In spectral CT …
an object, extending a conventional image volume with a spectral dimension. In spectral CT …
Spectral CT reconstruction with image sparsity and spectral mean
Photon-counting detectors can acquire x-ray intensity data in different energy bins. The
signal-to-noise ratio of resultant raw data in each energy bin is generally low due to the …
signal-to-noise ratio of resultant raw data in each energy bin is generally low due to the …
Non-local low-rank cube-based tensor factorization for spectral CT reconstruction
Spectral computed tomography (CT) reconstructs material-dependent attenuation images
from the projections of multiple narrow energy windows, which is meaningful for material …
from the projections of multiple narrow energy windows, which is meaningful for material …
Iterative material decomposition for spectral CT using self-supervised Noise2Noise prior
Compared to conventional computed tomography (CT), spectral CT can provide the
capability of material decomposition, which can be used in many clinical diagnosis …
capability of material decomposition, which can be used in many clinical diagnosis …
Spectral CT reconstruction—ASSIST: Aided by self-similarity in image-spectral tensors
Spectral computed tomography (CT) reconstructs multienergy images from data in different
energy bins. However, these reconstructed images can be contaminated by noise due to the …
energy bins. However, these reconstructed images can be contaminated by noise due to the …
A dynamic material discrimination algorithm for dual MV energy X-ray digital radiography
L Li, R Li, S Zhang, T Zhao, Z Chen - Applied Radiation and Isotopes, 2016 - Elsevier
Dual-energy X-ray radiography has become a well-established technique in medical,
industrial, and security applications, because of its material or tissue discrimination …
industrial, and security applications, because of its material or tissue discrimination …
FONT-SIR: Fourth-order nonlocal tensor decomposition model for spectral CT image reconstruction
X Chen, W **a, Y Liu, H Chen, J Zhou… - … on Medical Imaging, 2022 - ieeexplore.ieee.org
Spectral computed tomography (CT) reconstructs images from different spectral data
through photon counting detectors (PCDs). However, due to the limited number of photons …
through photon counting detectors (PCDs). However, due to the limited number of photons …
Robust multimaterial decomposition of spectral CT using convolutional neural networks
Z Chen, L Li - Optical Engineering, 2019 - spiedigitallibrary.org
Spectral computed tomography (CT) can reconstruct scanned objects at different energy-
bins and thus solve the multimaterial decomposition (MMD) problem. Because the linear …
bins and thus solve the multimaterial decomposition (MMD) problem. Because the linear …
Image‐domain multimaterial decomposition for dual‐energy CT based on prior information of material images
Purpose Dual‐Energy Computed Tomography (DECT) is of great interest in medical
imaging, security inspection, and nondestructive testing. Most DECT reconstruction methods …
imaging, security inspection, and nondestructive testing. Most DECT reconstruction methods …