Comparison of projection domain, image domain, and comprehensive deep learning for sparse-view X-ray CT image reconstruction

K Liang, H Yang, Y Xing - arXiv preprint arXiv:1804.04289, 2018 - arxiv.org
X-ray Computed Tomography (CT) imaging has been widely used in clinical diagnosis, non-
destructive examination, and public safety inspection. Sparse-view (sparse view) CT has …

LRR-CED: Low-resolution reconstruction-aware convolutional encoder–decoder network for direct sparse-view CT image reconstruction

VSS Kandarpa, A Perelli, A Bousse… - Physics in Medicine & …, 2022 - iopscience.iop.org
Objective. Sparse-view computed tomography (CT) reconstruction has been at the forefront
of research in medical imaging. Reducing the total x-ray radiation dose to the patient while …

[HTML][HTML] Attention-based dual-branch deep network for sparse-view computed tomography image reconstruction

X Gao, T Su, Y Zhang, J Zhu, Y Tan, H Cui… - … Imaging in Medicine …, 2023 - ncbi.nlm.nih.gov
Background The widespread application of X-ray computed tomography (CT) imaging in
medical screening makes radiation safety a major concern for public health. Sparse-view CT …

Hybrid-domain neural network processing for sparse-view CT reconstruction

D Hu, J Liu, T Lv, Q Zhao, Y Zhang… - … on Radiation and …, 2020 - ieeexplore.ieee.org
X-ray computed tomography (CT) is one of the most widely used tools in medical imaging,
industrial nondestructive testing, lesion detection, and other applications. However …

PARS-NET: a novel deep learning framework using parallel residual conventional neural networks for sparse-view CT reconstruction

H Khodajou-Chokami, SA Hosseini… - Journal of …, 2022 - iopscience.iop.org
Sparse-view computed tomography (CT) is recently proposed as a promising method to
speed up data acquisition and alleviate the issue of CT high dose delivery to the patients …

An attention-based deep convolutional neural network for ultra-sparse-view CT reconstruction

Y Chan, X Liu, T Wang, J Dai, Y Xie, X Liang - Computers in Biology and …, 2023 - Elsevier
Abstract X-ray Computed Tomography (CT) techniques play a vitally important role in clinical
diagnosis, but radioactivity exposure can also induce the risk of cancer for patients. Sparse …

Artifact removal using improved GoogLeNet for sparse-view CT reconstruction

S Xie, X Zheng, Y Chen, L Xie, J Liu, Y Zhang, J Yan… - Scientific reports, 2018 - nature.com
Sparse-view Reconstruction can be used to provide accelerated low dose CT imaging with
both accelerated scan and reduced projection/back-projection calculation. Despite the rapid …

Sparse-view CT reconstruction via generative adversarial networks

Z Zhao, Y Sun, P Cong - 2018 IEEE Nuclear Science …, 2018 - ieeexplore.ieee.org
Low dose and sparse view CT are effective approaches to reduce the radiation dose and
accelerate scan speed. Images reconstructed from insufficient data acquired from low dose …

Sparse-view and limited-angle CT reconstruction with untrained networks and deep image prior

Z Shu, A Entezari - Computer Methods and Programs in Biomedicine, 2022 - Elsevier
Background and objective: Neural network based image reconstruction methods are
becoming increasingly popular. However, limited training data and the lack of theoretical …

Generative modeling in sinogram domain for sparse-view CT reconstruction

B Guan, C Yang, L Zhang, S Niu… - … on Radiation and …, 2023 - ieeexplore.ieee.org
The radiation dose in computed tomography (CT) examinations is harmful for patients but
can be significantly reduced by intuitively decreasing the number of projection views …