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 …
Low‐dose CT image denoising with improving WGAN and hybrid loss function
Z Li, W Shi, Q Xing, Y Miao, W He… - … Methods in Medicine, 2021 - Wiley Online Library
The X‐ray radiation from computed tomography (CT) brought us the potential risk. Simply
decreasing the dose makes the CT images noisy and diagnostic performance compromised …
decreasing the dose makes the CT images noisy and diagnostic performance compromised …
Image denoising for low-dose CT via convolutional dictionary learning and neural network
R Yan, Y Liu, Y Liu, L Wang, R Zhao… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Removing noise and artifacts from low-dose computed tomography (LDCT) is a challenging
task, and most existing image-based algorithms tend to blur the results. To improve the …
task, and most existing image-based algorithms tend to blur the results. To improve the …
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 …
Low-dose CT image denoising using a generative adversarial network with Wasserstein distance and perceptual loss
The continuous development and extensive use of computed tomography (CT) in medical
practice has raised a public concern over the associated radiation dose to the patient …
practice has raised a public concern over the associated radiation dose to the patient …
Structurally-sensitive multi-scale deep neural network for low-dose CT denoising
Computed tomography (CT) is a popular medical imaging modality and enjoys wide clinical
applications. At the same time, the X-ray radiation dose associated with CT scannings raises …
applications. At the same time, the X-ray radiation dose associated with CT scannings raises …
Deep learning for low-dose CT denoising using perceptual loss and edge detection layer
M Gholizadeh-Ansari, J Alirezaie, P Babyn - Journal of digital imaging, 2020 - Springer
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 …
SACNN: Self-attention convolutional neural network for low-dose CT denoising with self-supervised perceptual loss network
Computed tomography (CT) is a widely used screening and diagnostic tool that allows
clinicians to obtain a high-resolution, volumetric image of internal structures in a non …
clinicians to obtain a high-resolution, volumetric image of internal structures in a non …
Investigation of low-dose CT image denoising using unpaired deep learning methods
Low-dose computed tomography (LDCT) is desired due to prevalence and ionizing radiation
of CT, but suffers elevated noise. To improve LDCT image quality, an image-domain …
of CT, but suffers elevated noise. To improve LDCT image quality, an image-domain …
CT image denoising with perceptive deep neural networks
Increasing use of CT in modern medical practice has raised concerns over associated
radiation dose. Reduction of radiation dose associated with CT can increase noise and …
radiation dose. Reduction of radiation dose associated with CT can increase noise and …