Advances in medical image analysis with vision transformers: a comprehensive review

R Azad, A Kazerouni, M Heidari, EK Aghdam… - Medical Image …, 2023 - Elsevier
The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …

Recent progress in transformer-based medical image analysis

Z Liu, Q Lv, Z Yang, Y Li, CH Lee, L Shen - Computers in Biology and …, 2023 - Elsevier
The transformer is primarily used in the field of natural language processing. Recently, it has
been adopted and shows promise in the computer vision (CV) field. Medical image analysis …

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 …

DU-GAN: Generative adversarial networks with dual-domain U-Net-based discriminators for low-dose CT denoising

Z Huang, J Zhang, Y Zhang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Low-dose computed tomography (LDCT) has drawn major attention in the medical imaging
field due to the potential health risks of CT-associated X-ray radiation to patients. Reducing …

Solving inverse problems with latent diffusion models via hard data consistency

B Song, SM Kwon, Z Zhang, X Hu, Q Qu… - arXiv preprint arXiv …, 2023 - arxiv.org
Diffusion models have recently emerged as powerful generative priors for solving inverse
problems. However, training diffusion models in the pixel space are both data intensive and …

Low-dose CT denoising via sinogram inner-structure transformer

L Yang, Z Li, R Ge, J Zhao, H Si… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Low-Dose Computed Tomography (LDCT) technique, which reduces the radiation harm to
human bodies, is now attracting increasing interest in the medical imaging field. As the …

CoreDiff: Contextual error-modulated generalized diffusion model for low-dose CT denoising and generalization

Q Gao, Z Li, J Zhang, Y Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Low-dose computed tomography (CT) images suffer from noise and artifacts due to photon
starvation and electronic noise. Recently, some works have attempted to use diffusion …

CycleGAN denoising of extreme low-dose cardiac CT using wavelet-assisted noise disentanglement

J Gu, TS Yang, JC Ye, DH Yang - Medical image analysis, 2021 - Elsevier
In electrocardiography (ECG) gated cardiac CT angiography (CCTA), multiple images
covering the entire cardiac cycle are taken continuously, so reduction of the accumulated …

DDPTransformer: dual-domain with parallel transformer network for sparse view CT image reconstruction

R Li, Q Li, H Wang, S Li, J Zhao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Computed tomography (CT) is increasingly essential for clinical diagnosis nowadays while
X-ray ionizing radiation is harmful and may increase the risk of cancers. Researchers have …

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 …