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 …
Domain progressive 3D residual convolution network to improve low-dose CT imaging
The wide applications of X-ray computed tomography (CT) bring low-dose CT (LDCT) into a
clinical prerequisite, but reducing the radiation exposure in CT often leads to significantly …
clinical prerequisite, but reducing the radiation exposure in CT often leads to significantly …
Low-dose CT denoising via sinogram inner-structure transformer
Low-Dose Computed Tomography (LDCT) technique, which reduces the radiation harm to
human bodies, is now attracting increasing interest in the medical imaging field. As the …
human bodies, is now attracting increasing interest in the medical imaging field. As the …
Deep iterative reconstruction estimation (DIRE): approximate iterative reconstruction estimation for low dose CT imaging
The image quality in low dose computed tomography (LDCT) can be severely degraded by
amplified mottle noise and streak artifacts. Although the iterative reconstruction (IR) …
amplified mottle noise and streak artifacts. Although the iterative reconstruction (IR) …
An adaptive self-guided wavelet convolutional neural network with compound loss for low-dose CT denoising
S Li, Q Li, R Li, W Wu, J Zhao, Y Qiang… - … Signal Processing and …, 2022 - Elsevier
Computed Tomography (CT) is an imaging method widely used in clinical, industrial, and
other applications. Furthermore, it is one of the common methods of modern clinical medical …
other applications. Furthermore, it is one of the common methods of modern clinical medical …
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 …
A feasibility study of extracting tissue textures from a previous full-dose CT database as prior knowledge for Bayesian reconstruction of current low-dose CT images
Y Gao, Z Liang, W Moore, H Zhang… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Markov random field (MRF) has been widely used to incorporate a priori knowledge as
penalty or regularizer to preserve edge sharpness while smoothing the region enclosed by …
penalty or regularizer to preserve edge sharpness while smoothing the region enclosed by …
Efficient low-dose CT denoising by locally-consistent non-local means (LC-NLM)
The never-ending quest for lower radiation exposure is a major challenge to the image
quality of advanced CT scans. Post-processing algorithms have been recently proposed to …
quality of advanced CT scans. Post-processing algorithms have been recently proposed to …
[PDF][PDF] Low-dose CT streak artifacts removal using deep residual neural network
In order to effectively reduce the risk of radiation exposure, low-dose CT using fewer
projection views is becoming more and more preferred recently although it suffers …
projection views is becoming more and more preferred recently although it suffers …