Systematic review on learning-based spectral CT
Spectral computed tomography (CT) has recently emerged as an advanced version of
medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two …
medical CT and significantly improves conventional (single-energy) CT. Spectral CT has two …
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 …
Self-supervised nonlinear transform-based tensor nuclear norm for multi-dimensional image recovery
Recently, transform-based tensor nuclear norm (TNN) minimization methods have received
increasing attention for recovering third-order tensors in multi-dimensional imaging …
increasing attention for recovering third-order tensors in multi-dimensional imaging …
Deep learning based spectral CT imaging
Spectral computed tomography (CT) has attracted much attention in radiation dose
reduction, metal artifacts removal, tissue quantification and material discrimination. The x-ray …
reduction, metal artifacts removal, tissue quantification and material discrimination. The x-ray …
Hypernetwork-based physics-driven personalized federated learning for CT imaging
In clinical practice, computed tomography (CT) is an important noninvasive inspection
technology to provide patients' anatomical information. However, its potential radiation risk is …
technology to provide patients' anatomical information. However, its potential radiation risk is …
Hypernetwork-based personalized federated learning for multi-institutional CT imaging
Computed tomography (CT) is of great importance in clinical practice due to its powerful
ability to provide patients' anatomical information without any invasive inspection, but its …
ability to provide patients' anatomical information without any invasive inspection, but its …
CD-Net: Comprehensive domain network with spectral complementary for DECT sparse-view reconstruction
Dual-energy computed tomography (DECT) is of great clinical significance because of its
material identification and quantification capacity. Although DECT measures attenuation …
material identification and quantification capacity. Although DECT measures attenuation …
Physics-/model-based and data-driven methods for low-dose computed tomography: A survey
Since 2016, deep learning (DL) has advanced tomographic imaging with remarkable
successes, especially in low-dose computed tomography (LDCT) imaging. Despite being …
successes, especially in low-dose computed tomography (LDCT) imaging. Despite being …
Robust low-rank tensor ring completion
Low-rank tensor completion recovers missing entries based on different tensor
decompositions. Due to its outstanding performance in exploiting some higher-order data …
decompositions. Due to its outstanding performance in exploiting some higher-order data …
Tensor completion via collaborative sparse and low-rank transforms
The transform-based tensor nuclear norm (TNN) methods have recently yielded promising
results for tensor completion. The primary goal of these methods is to exploit the low-rank …
results for tensor completion. The primary goal of these methods is to exploit the low-rank …