Artifact Reduction in 3D and 4D Cone-beam Computed Tomography Images with Deep Learning-A Review
M Amirian, D Barco, I Herzig, FP Schilling - Ieee Access, 2024 - ieeexplore.ieee.org
Deep learning based approaches have been used to improve image quality in cone-beam
computed tomography (CBCT), a medical imaging technique often used in applications such …
computed tomography (CBCT), a medical imaging technique often used in applications such …
Iterative residual optimization network for limited-angle tomographic reconstruction
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 …
leading to edge divergence with degraded image quality. Recently, deep learning has been …
Spectral2Spectral: Image-spectral similarity assisted deep spectral CT reconstruction without reference
Spectral computed tomography based on a photon-counting detector (PCD) attracts more
and more attentions since it has the capability to provide more accurate identification and …
and more attentions since it has the capability to provide more accurate identification and …
Time-reversion fast-sampling score-based model for limited-angle ct reconstruction
The score-based generative model (SGM) has received significant attention in the field of
medical imaging, particularly in the context of limited-angle computed tomography (LACT) …
medical imaging, particularly in the context of limited-angle computed tomography (LACT) …
Two-and-a-half order score-based model for solving 3D ill-posed inverse problems
Abstract Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are crucial
technologies in the field of medical imaging. Score-based models demonstrated …
technologies in the field of medical imaging. Score-based models demonstrated …
Training Generative Image Super-Resolution Models by Wavelet-Domain Losses Enables Better Control of Artifacts
Super-resolution (SR) is an ill-posed inverse problem where the size of the set of feasible
solutions that are consistent with a given low-resolution image is very large. Many …
solutions that are consistent with a given low-resolution image is very large. Many …
Wavelet-inspired multi-channel score-based model for limited-angle CT reconstruction
J Zhang, H Mao, X Wang, Y Guo… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Score-based generative model (SGM) has demonstrated great potential in the challenging
limited-angle CT (LA-CT) reconstruction. SGM essentially models the probability density of …
limited-angle CT (LA-CT) reconstruction. SGM essentially models the probability density of …
Stage-by-stage wavelet optimization refinement diffusion model for sparse-view CT reconstruction
K Xu, S Lu, B Huang, W Wu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Diffusion model has emerged as a potential tool to tackle the challenge of sparse-view CT
reconstruction, displaying superior performance compared to conventional methods …
reconstruction, displaying superior performance compared to conventional methods …
Blind ct image quality assessment using ddpm-derived content and transformer-based evaluator
Lowering radiation dose per view and utilizing sparse views per scan are two common CT
scan modes, albeit often leading to distorted images characterized by noise and streak …
scan modes, albeit often leading to distorted images characterized by noise and streak …
Deep convolutional dictionary learning network for sparse view CT reconstruction with a group sparse prior
Purpose Numerous techniques based on deep learning have been utilized in sparse view
computed tomography (CT) imaging. Nevertheless, the majority of techniques are …
computed tomography (CT) imaging. Nevertheless, the majority of techniques are …