A Hybrid Framework of Dual-Domain Signal Restoration and Multi-depth Feature Reinforcement for Low-Dose Lung CT Denoising
J Chi, Z Sun, S Tian, H Wang, S Wang - Journal of Imaging Informatics in …, 2024 - Springer
Low-dose computer tomography (LDCT) has been widely used in medical diagnosis.
Various denoising methods have been presented to remove noise in LDCT scans. However …
Various denoising methods have been presented to remove noise in LDCT scans. However …
[HTML][HTML] Structure-preserving low-dose computed tomography image denoising using a deep residual adaptive global context attention network
Y Zhang, D Hao, Y Lin, W Sun, J Zhang… - … Imaging in Medicine …, 2023 - ncbi.nlm.nih.gov
Background Low-dose computed tomography (LDCT) scans can effectively reduce the
radiation damage to patients, but this is highly detrimental to CT image quality. Deep …
radiation damage to patients, but this is highly detrimental to CT image quality. Deep …
Low Dose CT Denoising by ResNet With Fused Attention Modules and Integrated Loss Functions
X-ray computed tomography (CT) is a non-invasive medical diagnostic tool that has raised
public concerns due to the associated health risks of radiation dose to patients. Reducing …
public concerns due to the associated health risks of radiation dose to patients. Reducing …
GCN-MIF: Graph Convolutional Network with Multi-Information Fusion for Low-dose CT Denoising
K Chen, J Sun, J Shen, J Luo, X Zhang, X Pan… - arXiv preprint arXiv …, 2021 - arxiv.org
Being low-level radiation exposure and less harmful to health, low-dose computed
tomography (LDCT) has been widely adopted in the early screening of lung cancer and …
tomography (LDCT) has been widely adopted in the early screening of lung cancer and …
Low dose ct denoising by resnet with fused attention modules and integrated loss functions
X-ray computed tomography (CT) is a non-invasive medical diagnostic tool that has raised
public concerns due to the associated health risks of radiation dose to patients. Reducing …
public concerns due to the associated health risks of radiation dose to patients. Reducing …
Multi-scale hierarchy feature fusion generative adversarial network for low-dose CT denoising
Image noise is an inherent issue in low-dose CT (LDCT). Increasing radiation dose can
alleviate this problem to some extent, but it also brings potential risks to the patients. Thus …
alleviate this problem to some extent, but it also brings potential risks to the patients. Thus …
Ted-net: Convolution-free t2t vision transformer-based encoder-decoder dilation network for low-dose ct denoising
Low dose computed tomography (CT) is a mainstream for clinical applications. However,
compared to normal dose CT, in the low dose CT (LDCT) images, there are stronger noise …
compared to normal dose CT, in the low dose CT (LDCT) images, there are stronger noise …
Mm-net: Multiframe and multimask-based unsupervised deep denoising for low-dose computed tomography
SY Jeon, W Kim, JH Choi - IEEE Transactions on Radiation …, 2022 - ieeexplore.ieee.org
Low-dose computed tomography (LDCT) is crucial due to the risk of radiation exposure to
patients. However, the high noise level in LDCT images may reduce the image quality …
patients. However, the high noise level in LDCT images may reduce the image quality …
Self‐adaption and texture generation: A hybrid loss function for low‐dose CT denoising
Background Deep learning has been successfully applied to low‐dose CT (LDCT)
denoising. But the training of the model is very dependent on an appropriate loss function …
denoising. But the training of the model is very dependent on an appropriate loss function …
Low-dose CT lung images denoising based on multiscale parallel convolution neural network
X Jiang, Y Jin, Y Yao - The Visual Computer, 2021 - Springer
The continuous development and wide application of CT in medical practice have raised
public concern over the associated radiation dose to the patient. However, reducing the …
public concern over the associated radiation dose to the patient. However, reducing the …