Applications of nonlocal means algorithm in low‐dose X‐ray CT image processing and reconstruction: a review
Low‐dose X‐ray computed tomography (LDCT) imaging is highly recommended for use in
the clinic because of growing concerns over excessive radiation exposure. However, the CT …
the clinic because of growing concerns over excessive radiation exposure. However, the CT …
Sharpness-aware low-dose CT denoising using conditional generative adversarial network
Low-dose computed tomography (LDCT) has offered tremendous benefits in radiation-
restricted applications, but the quantum noise as resulted by the insufficient number of …
restricted applications, but the quantum noise as resulted by the insufficient number of …
Regularization strategies in statistical image reconstruction of low‐dose x‐ray CT: A review
Statistical image reconstruction (SIR) methods have shown potential to substantially improve
the image quality of low‐dose x‐ray computed tomography (CT) as compared to the …
the image quality of low‐dose x‐ray computed tomography (CT) as compared to the …
Discriminative feature representation to improve projection data inconsistency for low dose CT imaging
In low dose computed tomography (LDCT) imaging, the data inconsistency of measured
noisy projections can significantly deteriorate reconstruction images. To deal with this …
noisy projections can significantly deteriorate reconstruction images. To deal with this …
Artifact correction in low‐dose dental CT imaging using Wasserstein generative adversarial networks
Purpose In recent years, health risks concerning high‐dose x‐ray radiation have become a
major concern in dental computed tomography (CT) examinations. Therefore, adopting low …
major concern in dental computed tomography (CT) examinations. Therefore, adopting low …
CCN-CL: A content-noise complementary network with contrastive learning for low-dose computed tomography denoising
Y Tang, Q Du, J Wang, Z Wu, Y Li, M Li, X Yang… - Computers in Biology …, 2022 - Elsevier
In recent years, low-dose computed tomography (LDCT) has played an increasingly
important role in the diagnosis CT to reduce the potential adverse effects of x-ray radiation …
important role in the diagnosis CT to reduce the potential adverse effects of x-ray radiation …
Deep cascade residual networks (DCRNs): optimizing an encoder–decoder convolutional neural network for low-dose CT imaging
To suppress noise and artifacts caused by the reduced radiation exposure in low-dose
computed tomography, several deep learning (DL)-based image restoration methods have …
computed tomography, several deep learning (DL)-based image restoration methods have …
Segmentation-guided denoising network for low-dose CT imaging
Z Huang, Z Liu, P He, Y Ren, S Li, Y Lei, D Luo… - Computer Methods and …, 2022 - Elsevier
Background: To reduce radiation exposure and improve diagnosis in low-dose computed
tomography, several deep learning (DL)-based image denoising methods have been …
tomography, several deep learning (DL)-based image denoising methods have been …
A self-supervised guided knowledge distillation framework for unpaired low-dose CT image denoising
J Wang, Y Tang, Z Wu, Q Du, L Yao, X Yang… - … medical imaging and …, 2023 - Elsevier
Low-dose computed tomography (LDCT) can significantly reduce the damage of X-ray to the
human body, but the reduction of CT dose will produce images with severe noise and …
human body, but the reduction of CT dose will produce images with severe noise and …
Nonlocal low-rank and sparse matrix decomposition for spectral CT reconstruction
Spectral computed tomography (CT) has been a promising technique in research and clinics
because of its ability to produce improved energy resolution images with narrow energy …
because of its ability to produce improved energy resolution images with narrow energy …