Photon-counting x-ray detectors for CT
The introduction of photon-counting detectors is expected to be the next major breakthrough
in clinical x-ray computed tomography (CT). During the last decade, there has been …
in clinical x-ray computed tomography (CT). During the last decade, there has been …
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 …
A material decomposition method for dual‐energy CT via dual interactive Wasserstein generative adversarial networks
Z Shi, H Li, Q Cao, Z Wang, M Cheng - Medical physics, 2021 - Wiley Online Library
Purpose Dual‐energy computed tomography (DECT) is highly promising for material
characterization and identification, whereas reconstructed material‐specific images are …
characterization and identification, whereas reconstructed material‐specific images are …
Spectral CT image-domain material decomposition via sparsity residual prior and dictionary learning
T Zhang, H Yu, Y **, S Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The spectral computed tomography (CT) system based on a photon-counting detector (PCD)
can quantitatively analyze the material composition of the inspected object by material …
can quantitatively analyze the material composition of the inspected object by material …
Stabilizing deep tomographic reconstruction: Part A. Hybrid framework and experimental results
A recent PNAS paper reveals that several popular deep reconstruction networks are
unstable. Specifically, three kinds of instabilities were reported:(1) strong image artefacts …
unstable. Specifically, three kinds of instabilities were reported:(1) strong image artefacts …
Quaternion-based dictionary learning and saturation-value total variation regularization for color image restoration
Color image restoration is a critical task in imaging sciences. Most variational methods
regard the color image as a Euclidean vector or the direct combination of three monochrome …
regard the color image as a Euclidean vector or the direct combination of three monochrome …
Image-domain material decomposition for spectral CT using a generalized dictionary learning
The spectral computed tomography (CT) has huge advantages by providing accurate
material information. Unfortunately, due to the instability or overdetermination of the material …
material information. Unfortunately, due to the instability or overdetermination of the material …
[PDF][PDF] Stabilizing deep tomographic reconstruction networks
Tomographic image reconstruction with deep learning (DL) is an emerging field of applied
artificial intelligence, but a recent landmark study reveals that several deep reconstruction …
artificial intelligence, but a recent landmark study reveals that several deep reconstruction …
Improved material decomposition with a two-step regularization for spectral CT
One of the advantages of spectral computed tomography (CT) is it can achieve accurate
material components using the material decomposition methods. The image-based material …
material components using the material decomposition methods. The image-based material …
Tomographic absorption spectroscopy based on dictionary learning
Tomographic absorption spectroscopy (TAS) has an advantage over other optical imaging
methods for practical combustor diagnostics: optical access is needed in a single plane only …
methods for practical combustor diagnostics: optical access is needed in a single plane only …