Limited parameter denoising for low‐dose X‐ray computed tomography using deep reinforcement learning
Background The use of deep learning has successfully solved several problems in the field
of medical imaging. Deep learning has been applied to the CT denoising problem …
of medical imaging. Deep learning has been applied to the CT denoising problem …
Denoising computed tomography images with 3D-convolution based neural networks
S Moilanen - 2021 - oulurepo.oulu.fi
Low-dose computed tomography (CT) is an imaging technique used in imaging cross-
sectional images of the body that minimizes the radiation dose of the patient. Low-dose CT …
sectional images of the body that minimizes the radiation dose of the patient. Low-dose CT …
Unpaired image denoising using a generative adversarial network in X-ray CT
This paper proposes a deep learning-based denoising method for noisy low-dose
computerized tomography (CT) images in the absence of paired training data. The proposed …
computerized tomography (CT) images in the absence of paired training data. The proposed …
Toward iterative reconstruction in clinical CT: increased sharpness-to-noise and significant dose reduction owing to a new class of regularization priors
H Bruder, R Raupach, M Sedlmair… - … 2010: Physics of …, 2010 - spiedigitallibrary.org
In this paper, a novel regularization approach for (non-statistical) iterative reconstruction is
developed. In our implementation, the update equation of iterative reconstruction is based …
developed. In our implementation, the update equation of iterative reconstruction is based …
Probabilistic self‐learning framework for low‐dose CT denoising
Purpose Despite the indispensable role of x‐ray computed tomography (CT) in diagnostic
medicine, the associated harmful ionizing radiation dose is a major concern, as it may cause …
medicine, the associated harmful ionizing radiation dose is a major concern, as it may cause …
Multi-stage Deep Learning Artifact Reduction for Computed Tomography
In Computed Tomography (CT), an image of the interior structure of an object is computed
from a set of acquired projection images. The quality of these reconstructed images is …
from a set of acquired projection images. The quality of these reconstructed images is …
[HTML][HTML] Low-cost probabilistic 3D denoising with applications for ultra-low-radiation computed tomography
We propose a pipeline for synthetic generation of personalized Computer Tomography (CT)
images, with a radiation exposure evaluation and a lifetime attributable risk (LAR) …
images, with a radiation exposure evaluation and a lifetime attributable risk (LAR) …
Ascon: Anatomy-aware supervised contrastive learning framework for low-dose ct denoising
While various deep learning methods have been proposed for low-dose computed
tomography (CT) denoising, most of them leverage the normal-dose CT images as the …
tomography (CT) denoising, most of them leverage the normal-dose CT images as the …
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 …
by reducing the X-ray dose. However, CT images reconstructed from low-dose X-rays …
Low dose CT image denoising using deep convolutional neural networks with extended receptive fields
N Thanh-Trung, DH Trinh, N Linh-Trung, M Luong - Authorea Preprints, 2023 - techrxiv.org
How to reduce dose radiation while preserving the image quality as when using standard
dose is one of the most important topics in the Computed Tomography (CT) imaging domain …
dose is one of the most important topics in the Computed Tomography (CT) imaging domain …