Advances in metal artifact reduction in CT images: A review of traditional and novel metal artifact reduction techniques

M Selles, JAC van Osch, M Maas, MF Boomsma… - European Journal of …, 2024 - Elsevier
Metal artifacts degrade CT image quality, hampering clinical assessment. Numerous metal
artifact reduction methods are available to improve the image quality of CT images with …

Solving inverse problems in medical imaging with score-based generative models

Y Song, L Shen, L Xing, S Ermon - arXiv preprint arXiv:2111.08005, 2021 - arxiv.org
Reconstructing medical images from partial measurements is an important inverse problem
in Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Existing solutions …

A review of deep learning ct reconstruction from incomplete projection data

T Wang, W Xia, J Lu, Y Zhang - IEEE Transactions on Radiation …, 2023 - ieeexplore.ieee.org
Computed tomography (CT) is a widely used imaging technique in both medical and
industrial applications. However, accurate CT reconstruction requires complete projection …

CBCT‐Based synthetic CT image generation using conditional denoising diffusion probabilistic model

J Peng, RLJ Qiu, JF Wynne, CW Chang, S Pan… - Medical …, 2024 - Wiley Online Library
Background Daily or weekly cone‐beam computed tomography (CBCT) scans are
commonly used for accurate patient positioning during the image‐guided radiotherapy …

TransCT: dual-path transformer for low dose computed tomography

Z Zhang, L Yu, X Liang, W Zhao, L Xing - … 1, 2021, Proceedings, Part VI 24, 2021 - Springer
Low dose computed tomography (LDCT) has attracted more and more attention in routine
clinical diagnosis assessment, therapy planning, etc., which can reduce the dose of X-ray …

DuDoDR-Net: Dual-domain data consistent recurrent network for simultaneous sparse view and metal artifact reduction in computed tomography

B Zhou, X Chen, SK Zhou, JS Duncan, C Liu - Medical Image Analysis, 2022 - Elsevier
Sparse-view computed tomography (SVCT) aims to reconstruct a cross-sectional image
using a reduced number of x-ray projections. While SVCT can efficiently reduce the radiation …

Dual-energy CT based mass density and relative stopping power estimation for proton therapy using physics-informed deep learning

CW Chang, Y Gao, T Wang, Y Lei… - Physics in Medicine …, 2022 - iopscience.iop.org
Proton therapy requires accurate dose calculation for treatment planning to ensure the
conformal doses are precisely delivered to the targets. The conversion of CT numbers to …

InDuDoNet: An interpretable dual domain network for CT metal artifact reduction

H Wang, Y Li, H Zhang, J Chen, K Ma, D Meng… - … Image Computing and …, 2021 - Springer
For the task of metal artifact reduction (MAR), although deep learning (DL)-based methods
have achieved promising performances, most of them suffer from two problems: 1) the CT …

DICDNet: deep interpretable convolutional dictionary network for metal artifact reduction in CT images

H Wang, Y Li, N He, K Ma, D Meng… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Computed tomography (CT) images are often impaired by unfavorable artifacts caused by
metallic implants within patients, which would adversely affect the subsequent clinical …

Unsupervised polychromatic neural representation for ct metal artifact reduction

Q Wu, L Chen, C Wang, H Wei… - Advances in …, 2023 - proceedings.neurips.cc
Emerging neural reconstruction techniques based on tomography (eg, NeRF, NeAT, and
NeRP) have started showing unique capabilities in medical imaging. In this work, we …