Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives

J Li, J Chen, Y Tang, C Wang, BA Landman… - Medical image …, 2023 - Elsevier
Transformer, one of the latest technological advances of deep learning, has gained
prevalence in natural language processing or computer vision. Since medical imaging bear …

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 …

DOLCE: A model-based probabilistic diffusion framework for limited-angle ct reconstruction

J Liu, R Anirudh, JJ Thiagarajan, S He… - Proceedings of the …, 2023 - openaccess.thecvf.com
Abstract Limited-Angle Computed Tomography (LACT) is a non-destructive 3D imaging
technique used in a variety of applications ranging from security to medicine. The limited …

DIOR: Deep iterative optimization-based residual-learning for limited-angle CT reconstruction

D Hu, Y Zhang, J Liu, S Luo… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Limited-angle CT is a challenging problem in real applications. Incomplete projection data
will lead to severe artifacts and distortions in reconstruction images. To tackle this problem …

Iterative residual optimization network for limited-angle tomographic reconstruction

J Pan, H Yu, Z Gao, S Wang, H Zhang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Limited-angle tomographic reconstruction is one of the typical ill-posed inverse problems,
leading to edge divergence with degraded image quality. Recently, deep learning has been …

DuDoTrans: dual-domain transformer for sparse-view CT reconstruction

C Wang, K Shang, H Zhang, Q Li, SK Zhou - International Workshop on …, 2022 - Springer
Abstract While Computed Tomography (CT) is necessary for clinical diagnosis, ionizing
radiation in the imaging process induces irreversible injury, thereby driving researchers to …

DuDoTrans: dual-domain transformer provides more attention for sinogram restoration in sparse-view CT reconstruction

C Wang, K Shang, H Zhang, Q Li, Y Hui… - arxiv preprint arxiv …, 2021 - arxiv.org
While Computed Tomography (CT) reconstruction from X-ray sinograms is necessary for
clinical diagnosis, iodine radiation in the imaging process induces irreversible injury …

A review of deep learning ct reconstruction from incomplete projection data

T Wang, W **a, 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 …

DuDoUFNet: dual-domain under-to-fully-complete progressive restoration network for simultaneous metal artifact reduction and low-dose CT reconstruction

B Zhou, X Chen, H **e, SK Zhou… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
To reduce the potential risk of radiation to the patient, low-dose computed tomography
(LDCT) has been widely adopted in clinical practice for reconstructing cross-sectional …

InDuDoNet+: A deep unfolding dual domain network for metal artifact reduction in CT images

H Wang, Y Li, H Zhang, D Meng, Y Zheng - Medical Image Analysis, 2023 - Elsevier
During the computed tomography (CT) imaging process, metallic implants within patients
often cause harmful artifacts, which adversely degrade the visual quality of reconstructed CT …