Iterative low-dose CT reconstruction with priors trained by artificial neural network

D Wu, K Kim, G El Fakhri, Q Li - IEEE transactions on medical …, 2017 - ieeexplore.ieee.org
Dose reduction in computed tomography (CT) is essential for decreasing radiation risk in
clinical applications. Iterative reconstruction algorithms are one of the most promising way to …

Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstruction

H Shan, A Padole, F Homayounieh, U Kruger… - Nature Machine …, 2019 - nature.com
Commercial iterative reconstruction techniques help to reduce the radiation dose of
computed tomography (CT), but altered image appearance and artefacts can limit their …

Deep iterative reconstruction estimation (DIRE): approximate iterative reconstruction estimation for low dose CT imaging

J Liu, Y Zhang, Q Zhao, T Lv, W Wu, N Cai… - Physics in Medicine …, 2019 - iopscience.iop.org
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) …

Low‐dose CT reconstruction with Noise2Noise network and testing‐time fine‐tuning

D Wu, K Kim, Q Li - Medical Physics, 2021 - Wiley Online Library
Purpose Deep learning‐based image denoising and reconstruction methods demonstrated
promising performance on low‐dose CT imaging in recent years. However, most existing …

Deep learning-based image quality improvement for low-dose computed tomography simulation in radiation therapy

T Wang, Y Lei, Z Tian, X Dong, Y Liu… - Journal of Medical …, 2019 - spiedigitallibrary.org
Low-dose computed tomography (CT) is desirable for treatment planning and simulation in
radiation therapy. Multiple rescanning and replanning during the treatment course with a …

Low-dose CT via convolutional neural network

H Chen, Y Zhang, W Zhang, P Liao, K Li… - Biomedical optics …, 2017 - opg.optica.org
In order to reduce the potential radiation risk, low-dose CT has attracted an increasing
attention. However, simply lowering the radiation dose will significantly degrade the image …

Low-dose CT with a residual encoder-decoder convolutional neural network

H Chen, Y Zhang, MK Kalra, F Lin… - IEEE transactions on …, 2017 - ieeexplore.ieee.org
Given the potential risk of X-ray radiation to the patient, low-dose CT has attracted a
considerable interest in the medical imaging field. Currently, the main stream low-dose CT …

A deep convolutional neural network using directional wavelets for low‐dose X‐ray CT reconstruction

E Kang, J Min, JC Ye - Medical physics, 2017 - Wiley Online Library
Purpose Due to the potential risk of inducing cancer, radiation exposure by X‐ray CT
devices should be reduced for routine patient scanning. However, in low‐dose X‐ray CT …

Low-dose CT reconstruction via edge-preserving total variation regularization

Z Tian, X Jia, K Yuan, T Pan… - Physics in Medicine & …, 2011 - iopscience.iop.org
High radiation dose in computed tomography (CT) scans increases the lifetime risk of cancer
and has become a major clinical concern. Recently, iterative reconstruction algorithms with …

Computationally efficient deep neural network for computed tomography image reconstruction

D Wu, K Kim, Q Li - Medical physics, 2019 - Wiley Online Library
Purpose Deep neural network‐based image reconstruction has demonstrated promising
performance in medical imaging for undersampled and low‐dose scenarios. However, it …