3d residual convolutional neural network for low dose ct denoising
AA Zamyatin, L Yu, D Rozas - Medical Imaging 2022: Physics …, 2022 - spiedigitallibrary.org
CT continues to be one of the most widely used medical imaging modalities. Concerns
about long term effect of x-ray radiation on patients have led to efforts to reduce the x-ray …
about long term effect of x-ray radiation on patients have led to efforts to reduce the x-ray …
Benchmarking Deep Learning-Based Low Dose CT Image Denoising Algorithms
Long lasting efforts have been made to reduce radiation dose and thus the potential
radiation risk to the patient for computed tomography acquisitions without severe …
radiation risk to the patient for computed tomography acquisitions without severe …
Dictionary-based image denoising for dual energy computed tomography
Compared to conventional computed tomography (CT), dual energy CT allows for improved
material decomposition by conducting measurements at two distinct energy spectra. Since …
material decomposition by conducting measurements at two distinct energy spectra. Since …
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 …
Unsupervised domain adaptation for low-dose computed tomography denoising
Deep neural networks have shown great improvements in low-dose computed tomography
(CT) denoising. Early deep learning-based low-dose CT denoising algorithms were …
(CT) denoising. Early deep learning-based low-dose CT denoising algorithms were …
Low dose CT denoising via joint bilateral filtering and intelligent parameter optimization
Denoising of clinical CT images is an active area for deep learning research. Current
clinically approved methods use iterative reconstruction methods to reduce the noise in CT …
clinically approved methods use iterative reconstruction methods to reduce the noise in CT …
Deep Learning for Low-Dose CT Denoising
M Gholizadeh-Ansari, J Alirezaie, P Babyn - arXiv preprint arXiv …, 2019 - arxiv.org
Low-dose CT denoising is a challenging task that has been studied by many researchers.
Some studies have used deep neural networks to improve the quality of low-dose CT …
Some studies have used deep neural networks to improve the quality of low-dose CT …
Denoising for low-dose CT image by discriminative weighted nuclear norm minimization
L Jia, Q Zhang, Y Shang, Y Wang, Y Liu, N Wang… - IEEE …, 2018 - ieeexplore.ieee.org
Low-dose computed tomography (LDCT) is an effective approach to reduce radiation
exposure to patients. Lots of mottle noise and streak artifacts, however, are introduced to the …
exposure to patients. Lots of mottle noise and streak artifacts, however, are introduced to the …
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 …
reducing image noise in CT. Some of these methods showed promising results, especially in …
A cascaded convolutional neural network for x-ray low-dose CT image denoising
Image denoising techniques are essential to reducing noise levels and enhancing diagnosis
reliability in low-dose computed tomography (CT). Machine learning based denoising …
reliability in low-dose computed tomography (CT). Machine learning based denoising …