Advances in medical image analysis with vision transformers: a comprehensive review
The remarkable performance of the Transformer architecture in natural language processing
has recently also triggered broad interest in Computer Vision. Among other merits …
has recently also triggered broad interest in Computer Vision. Among other merits …
Recent progress in transformer-based medical image analysis
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 …
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
Reconstructing medical images from partial measurements is an important inverse problem
in Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Existing solutions …
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
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 …
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
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 …
problems. However, training diffusion models in the pixel space are both data intensive and …
Low-dose CT denoising via sinogram inner-structure transformer
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 …
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
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 …
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
In electrocardiography (ECG) gated cardiac CT angiography (CCTA), multiple images
covering the entire cardiac cycle are taken continuously, so reduction of the accumulated …
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 …
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
Purpose Deep learning‐based image denoising and reconstruction methods demonstrated
promising performance on low‐dose CT imaging in recent years. However, most existing …
promising performance on low‐dose CT imaging in recent years. However, most existing …