Preliminary denoising by 3D U-Net in image domain for low dose CT images

X Song, Y Han, X Xi, L Li, L Zhu, S Yang, M Liu… - 2022 2nd International …, 2022 - dl.acm.org
Low dose CT (LDCT) by reducing the X-ray tube current is of huge significance during
clinical scanning. However, low-dose CT images often have strong noise and artifacts …

An unsupervised two‐step training framework for low‐dose computed tomography denoising

W Kim, J Lee, JH Choi - Medical Physics, 2024 - Wiley Online Library
Background Although low‐dose computed tomography (CT) imaging has been more widely
adopted in clinical practice to reduce radiation exposure to patients, the reconstructed CT …

SCRDN: Residual dense network with self-calibrated convolutions for low dose CT image denoising

L Ma, H Xue, G Yang, Z Zhang, C Li, Y Yao… - Nuclear Instruments and …, 2023 - Elsevier
Low-dose computed tomography (LDCT) can reduce the X-ray radiation dose that the
patients receive, up to 86%, which decreases the potential hazards and expands its …

A preliminary study on projection denoising for low-dose CT imaging using modified dual-domain U-net

Z Feng, Z Li, A Cai, L Li, B Yan… - 2020 3rd International …, 2020 - ieeexplore.ieee.org
Recently, low-dose computed tomography (CT) was considered by many researchers to be
a good solution to reduce radiation risks of patients. However, lowering X-ray tube current …

HCformer: hybrid CNN-transformer for LDCT image denoising

J Yuan, F Zhou, Z Guo, X Li, H Yu - Journal of Digital Imaging, 2023 - Springer
Low-dose computed tomography (LDCT) is an effective way to reduce radiation exposure for
patients. However, it will increase the noise of reconstructed CT images and affect the …

Low-dose CT image denoising using classification densely connected residual network

J Ming, B Yi, Y Zhang, H Li - KSII Transactions on Internet and …, 2020 - koreascience.kr
Considering that high-dose X-ray radiation during CT scans may bring potential risks to
patients, in the medical imaging industry there has been increasing emphasis on low-dose …

Gradient extraction based multiscale dense cross network for LDCT denoising

J Kang, Y Liu, H Shu, N Guo, Q Zhang, Y Zhou… - Nuclear Instruments and …, 2023 - Elsevier
Low-dose computed tomography (LDCT) reduces the damage caused by ionizing radiation
by reducing the X-ray dose. However, CT images reconstructed from low-dose X-rays …

Low-dose CT image denoising via frequency division and encoder-dual decoder GAN

F Jiao, Z Gui, Y Liu, L Yao, P Zhang - Signal, Image and Video Processing, 2021 - Springer
Utilization of lower dose to generate CT images (LDCT) can reduce X-ray radiation damage
to human body, but the resulting noise and artifacts will hinder its applications for clinical …

Residual-based convolutional-neural-network (CNN) for low-dose CT denoising: impact of multi-slice input

Z Zhou, NR Huber, A Inoue… - Medical Imaging 2022 …, 2022 - spiedigitallibrary.org
Deep convolutional neural network (CNN) based methods have become popular choices for
reducing image noise in CT. Some of these methods showed promising results, especially in …

Noise2Context: context‐assisted learning 3D thin‐layer for low‐dose CT

Z Zhang, X Liang, W Zhao, L Xing - Medical Physics, 2021 - Wiley Online Library
Purpose Computed tomography (CT) has played a vital role in medical diagnosis,
assessment, and therapy planning, etc. In clinical practice, concerns about the increase of x …