Image denoising for low-dose CT via convolutional dictionary learning and neural network

R Yan, Y Liu, Y Liu, L Wang, R Zhao… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Removing noise and artifacts from low-dose computed tomography (LDCT) is a challenging
task, and most existing image-based algorithms tend to blur the results. To improve the …

Dual-domain collaborative diffusion sampling for multi-source stationary computed tomography reconstruction

Z Li, D Chang, Z Zhang, F Luo, Q Liu… - … on Medical Imaging, 2024 - ieeexplore.ieee.org
The multi-source stationary CT, where both the detector and X-ray source are fixed,
represents a novel imaging system with high temporal resolution that has garnered …

Estimating dual-energy CT imaging from single-energy CT data with material decomposition convolutional neural network

T Lyu, W Zhao, Y Zhu, Z Wu, Y Zhang, Y Chen… - Medical image …, 2021 - Elsevier
Dual-energy computed tomography (DECT) is of great significance for clinical practice due
to its huge potential to provide material-specific information. However, DECT scanners are …

CD-Net: Comprehensive domain network with spectral complementary for DECT sparse-view reconstruction

Y Zhang, T Lv, R Ge, Q Zhao, D Hu… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Dual-energy computed tomography (DECT) is of great clinical significance because of its
material identification and quantification capacity. Although DECT measures attenuation …

Single low-dose CT image denoising using a generative adversarial network with modified U-Net generator and multi-level discriminator

J Chi, C Wu, X Yu, P Ji, H Chu - IEEE Access, 2020 - ieeexplore.ieee.org
Low-dose CT (LDCT) images have been widely applied in the medical imaging field due to
the potential risk of exposing patients to X-ray radiations. Given the fact that reducing the …

PIE-ARNet: Prior image enhanced artifact removal network for limited-angle DECT

Y Zhang, D Hu, T Lyu, J Zhu, G Quan… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Dual-energy computed tomography (DECT) is of great clinical significance because it can
simultaneously visualize the internal structure of the scanned object and provide material …

Sparse-view cone beam CT reconstruction using dual CNNs in projection domain and image domain

L Chao, Z Wang, H Zhang, W Xu, P Zhang, Q Li - Neurocomputing, 2022 - Elsevier
Cone beam computed tomography (CBCT) is used extensively in image-guided surgery and
radiotherapy, but it induces ionizing radiation to the patients. Sparse-view CBCT is a main …

A generalizable new figure of merit for dose optimization in dual energy cone beam CT scanning protocols

C Li, L Zhou, J Deng, H Wu, R Wang… - Physics in Medicine …, 2023 - iopscience.iop.org
Objective. This study proposes and evaluates a new figure of merit (FOMn) for dose
optimization of Dual-energy cone-beam CT (DE-CBCT) scanning protocols based on size …

Fast and effective single‐scan dual‐energy cone‐beam CT reconstruction and decomposition denoising based on dual‐energy vectorization

X Jiang, C Fang, P Hu, H Cui, L Zhu, Y Yang - Medical physics, 2021 - Wiley Online Library
Purpose Flat‐panel detector (FPD) based dual‐energy cone‐beam computed tomography
(DE‐CBCT) is a promising imaging technique for dedicated clinical applications. In this …

Multi-scale feature fusion network for low-dose CT denoising

Z Li, Y Liu, H Shu, J Lu, J Kang, Y Chen, Z Gui - Journal of Digital Imaging, 2023 - Springer
Computed tomography (CT) is an imaging technique extensively used in medical treatment,
but too much radiation dose in a CT scan will cause harm to the human body. Decreasing …